Stuart Russell -- Publications

• Michael Dennis, Caspar Oesterheld, Vincent Conitzer, Andrew Critch, and Stuart Russell, How to Condition Behavior on Self-Referential Claims. In Proc. RLDM-25, 2025.
• Michael K. Cohen, Marcus Hutter, Yoshua Bengio, and Stuart Russell, RL, but don't do anything I wouldn't do. In Proc. UAI-25, 2025.
• Scott Emmons, Caspar Oesterheld, Vincent Conitzer, and Stuart Russell, Observation Interference in Partially Observable Assistance Games. In Proc. ICML-25, 2025.
• Cassidy Laidlaw, Eli Bronstein, Timothy Guo, Dylan Feng, Lukas Berglund, Justin Svegliato, Stuart Russell, and Anca Dragan, Scalably Solving Assistance Games. In Proc. ICML-25, 2025.
• Jiahai Feng, Stuart Russell, and Jacob Steinhardt, Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts. In Proc. ICML-25, 2025.
• Benjamin Plaut, Hanlin Zhu, Stuart Russell, Avoiding Catastrophe in Online Learning by Asking for Help. In Proc. ICML-25, 2025.
• Stuart Russell, Feedback on the Draft Report of the Joint California Policy Working Group on AI Frontier Models, April 8, 2025.
• Stuart Russell, Edson Prestes, Mohan Kankanhalli, Jibu Elias, Constanza Gómez Mont, Vilas Dhar, Adrian Weller, Pascale Fung, and Karim Beguir, AI red lines: The opportunities and challenges of setting limits. Emerging Technologies, World Economic Forum, 11 March 2025.
• Cassidy Laidlaw, Eli Bronstein, Timothy Guo, Dylan Feng, Lukas Berglund, Justin Svegliato, Stuart Russell, and Anca Dragan, Scalably solving assistance games. In Proc. ICLR-25 Workshop on Bidirectional Human-AI Alignment, 2025. (Best Paper Award)
• Jiahai Feng, Stuart Russell, and Jacob Steinhardt, Monitoring Latent World States in Language Models with Propositional Probes. In Proc. ICLR-25, 2025. (Spotlight)
• Shreyas Kapur, Erik Jenner, and Stuart Russell, Diffusion On Syntax Trees For Program Synthesis. (Spotlight) In Proc. ICLR-25, 2025.
• Aly Lidayan, Michael Dennis, and Stuart Russell BAMDP Shaping: a Unified Theoretical Framework for Intrinsic Motivation and Reward Shaping. In Proc. ICLR-25, 2025.
• Stuart Russell, DeepSeek, OpenAI, and the Race to Human Extinction, Newsweek, January 31, 2025.
• Andrew Garber, Rohan Subramani, Linus Luu, Mark Bedaywi, Stuart Russell, and Scott Emmons, The Partially Observable Off-Switch Game. In Proc. AAAI-25 (AI Alignment track).

• Stuart Russell and Peter Norvig, Umjetna inteligencija: Moderan pristup. (Croatian translation of Artificial Intelligence: A Modern Approach, fourth edition.) Translated by Boris Debić, Dorian Wild, and Marko Đurasević. Zagreb: Mate d.o.o., 2024.
• Scott Emmons, Caspar Oesterheld, Vincent Conitzer, and Stuart Russell, Observation Interference in Partially Observable Assistance Games, arXiv:2412.17797, December 2024.
• Francesca Rossi, Michael Schoenstein, and Stuart Russell, AI's potential futures: Mitigating risks, harnessing opportunities. In OECD Wonk Blog, December 19, 2024,
• Leon Lang, Davis Foote, Stuart Russell, Anca Dragan, Erik Jenner, and Scott Emmons, When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback. In Proc. NeurIPS-24, 2024.
• Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, and Stuart Russell, Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. In Proc. NeurIPS-24, 2024.
• Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael Jordan, Jiantao Jiao, Yuandong Tian, and Stuart Russell, Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. In Proc. NeurIPS-24, 2024.
• Alistair Knott, Dino Pedreschi, Toshiya Jitsuzumi, Susan Leavy, David Eyers, Tapabrata Chakraborti, Andrew Trotman, Sundar Sundareswaran, Ricardo Baeza-Yates, Przemyslaw Biecek, Adrian Weller, Paul D. Teal, Subhadip Basu, Mehmet Haklidir, Virginia Morini, Stuart Russell, and Yoshua Bengio, AI content detection in the emerging information ecosystem: New obligations for media and tech companies. Ethics and Information Technology, 26, 2024.
• Jiahai Feng, Stuart Russell, and Jacob Steinhardt, Monitoring latent world states in language models with propositional probes, arXiv:2406.19501, June 2024.
• Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, and Stuart Russell, Evidence of Learned Look-Ahead in a Chess-Playing Neural Network, arXiv:2406.00877, June 2024.
• Alistair Knott, Dino Pedreschi, Jonathan Stray, and Stuart Russell, The EU's Digital Services Act must provide researchers access to VLOPs' experimental protocols, Forum for Information and Democracy, June 2024.
• Shreyas Kapur, Erik Jenner, and Stuart Russell, Diffusion On Syntax Trees For Program Synthesis, arXiv:2405.20519, May 2024.
• Brian Judge, Mark Nitzberg, and Stuart Russell, When code isn't law: rethinking regulation for artificial intelligence. Policy and Society, puae020, 2024.
• Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, and Anca Dragan, AI Alignment with Changing and Influenceable Reward Functions, arXiv:2405.17713, May 2024.
• Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael Jordan, Jiantao Jiao, Yuandong Tian, and Stuart Russell, Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics, arXiv:2405.04669, May 2024.
• Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Trevor Darrell, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Baydin, Sheila Mcilraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca Dragan, Philip Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, and Sören Mindermann, Managing extreme AI risks amid rapid progress, Science, 384(6698), 842-845, 2024.
• Yoshua Bengio, Bronwyn Fox, (multiple authors), Stuart Russell, (multiple authors), International Scientific Report on the Safety of Advanced AI (Interim Report), Report No. DSIT 2024/009, UK Department for Science, Innovation and Technology, May 2024.
• David Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette Wing, and Joshua Tenenbaum, Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems, arXiv:2405.06624, May 2024.
• Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, and Anca Dragan, AI Alignment with Changing and Influenceable Reward Functions. In Proc. ICML-24, 2024.
• Luke Bailey, Euan Ong, Stuart Russell, and Scott Emmons, Image Hijacks: Adversarial Images can Control Generative Models at Runtime. In Proc. ICML-24, 2024.
• Vincent Conitzer, Rachel Freedman, Jobstq Heitzig, Wesley H. Holliday, Bob Jacobs, Nathan Lambert, Milan Mosse, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, and William Zwicker, Social Choice for AI Ethics and Safety. In Proc. ICML-24, 2024.
• Cassidy Laidlaw, Eli Bronstein, Timothy Guo, Dylan Feng, Lukas Berglund, Justin Svegliato, Stuart Russell, and Anca Dragan, Scalably Solving Assistance Games. In Proc. ICML 2024 Workshop on Models of Human Feedback for AI Alignment, 2024. Also in Proc. ICML 2024 Workshop on Next-Generation AI Safety, 2024.
• Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Moss, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, and William S. Zwicker, Social Choice for AI Alignment: Dealing with Diverse Human Feedback, arXiv:2404.10271, April 2024.
• Michael K. Cohen , Noam Kolt, Yoshua Bengio, Gillian K. Hadfield, And Stuart Russell, Regulating advanced artificial agents, Science, 384(6691), 36-38, 2024.
• Geoffrey Hinton, Andrew Yao, Yoshua Bengio, Ya-Qin Zhang, Fu Ying, Stuart Russell, Xue Lan, Gillian Hadfield, HongJiang Zhang, Tiejun Huang, Yi Zeng, Robert Trager, Kwok-Yan Lam, Dawn Song, Zhongyuan Wang, Dylan Hadfield-Menell, Yaodong Yang, Zhang Peng, Li Hang, Tian Tian, Edward Suning Tian, Toby Ord, Fynn Heide, and Adam Gleave, Consensus Statement on Red Lines in Artificial Intelligence. International Dialogue on AI Safety, Beijing, March, 2024.
• Evan Ellis, Gaurav Ghosal, Stuart Russell, Anca Dragan, and Erdem Biyik, A Generalized Acquisition Function for Preference-based Reward Learning. arXiv:2403.06003, March 2024.
• Jeremy Tien, Zhaojing Yang, Miru Jun, Stuart J. Russell, Anca Dragan, and Erdem Biyik, Optimizing Robot Behavior via Comparative Language Feedback. In Proc. 3rd Workshop on Human-Interactive Robot Learning (HIRL), HRI-24, Boulder, Colorado, 2024.
• Stuart Russell, Make AI safe or make safe AI?, UNESCO Global AI Ethics and Governance Observatory, February 2024.
• Leon Lang, Davis Foote, Stuart Russell, Anca Dragan, Erik Jenner, and Scott Emmons, When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning, arXiv:2402.17747, February 2024.
• Qingyuan Lu, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, and Stuart Russell, Ethically Compliant Autonomous Systems under Partial Observability. In Proc. ICRA-24, 2024.
• Hanlin Zhu, Baihe Huang, and Stuart Russell, On Representation Complexity of Model-based and Model-free Reinforcement Learning. In Proc. ICLR-24, 2024.
• Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, and Stuart Russell, Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. In Proc. ICLR-24, 2024.
• Cassidy Laidlaw, Banghua Zhu, Stuart Russell, and Anca Dragan, The Effective Horizon Explains Deep RL Performance in Stochastic Environments. In Proc. ICLR-24, 2024.
• Stuart Russell, Jonathan Reckford, Amy Brachio, Atle Hoie, Jane Nelson, Peter Maurer, Badr Jafar, and Jack Hidary, It's not all doom and gloom: 8 experts on their reasons to be optimistic in 2024, Davos Agenda, World Economic Forum, January 12, 2024.

• Cassidy Laidlaw, Stuart Russell, and Anca Dragan, Bridging RL Theory and Practice with the Effective Horizon, In Proc. NeurIPS-23, 2023.
• Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, and Stuart Russell, Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. In Proc. NeurIPS-23 Workshop on Robustness of Few-shot and Zero-shot Learning in Large Foundation Models, 2023.
• Julian Yocum, Phillip Christoffersen, Mehul Damani, Justin Svegliato, Dylan Hadfield-Menell, and Stuart Russell, Mitigating Generative Agent Social Dilemmas. In Proc. NeurIPS-23 Workshop on Foundation Models for Decision Making, 2023.
• Cassidy Laidlaw, Banghua Zhu, Stuart Russell, and Anca Dragan, The Effective Horizon Explains Deep RL Performance in Stochastic Environments. arXiv:2312.08369, December 2023.
• Edmund Mills, Shiye Su, Stuart Russell, and Scott Emmons, ALMANACS: A Simulatability Benchmark for Language Model Explainability, arXiv:2312.12747, December 2023.
• Stuart Russell, Written testimony for the United States Senate AI Forum on Risk, Alignment, & Guarding Against Doomsday Scenarios, Washington, DC, December 6, 2023.
• Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, and Stuart Russell, Tensor trust: Interpretable prompt injection attacks from an online game. arXiv:2311.01011, November 2023.
• Stuart Russell, Karine Perset, and Marko Grobelnik, Updates to the OECD's definition of an AI system explained, OECD AI Policy Observatory, November 29, 2023.
• Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Gunes Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca Dragan, Philip Torr, Stuart Russell, Daniel Kahnemann, Jan Brauner, and Soren Mindermann, Managing extreme AI risks amid rapid progress. arXiv:2310.17688, October 2023.
• Andrew Yao, Yoshua Bengio, Stuart Russell, Ya-Qin Zhang, Ed Felten, Roger Grosse, Gillian Hadfield, Sana Khareghani, Dylan Hadfield-Menell, Karine Perset, Dawn Song, Xin Chen, Max Tegmark, Elizabeth Seger, Yi Zeng, HongJiang Zhang, Yang-Hui He, Adam Gleave, and Fynn Heide, Statement. International Dialogue on AI Safety, Ditchley Park, UK, October, 2023.
• Rachel Freedman, Justin Svegliato, Kyle Wray, and Stuart Russell, Active teacher selection for reinforcement learning from human feedback. arXiv:2310.15288, October 2023.
• Hanlin Zhu, Baihe Huang, and Stuart Russell, On Representation Complexity of Model-based and Model-free Reinforcement Learning. arXiv:2310.01706, October 2023.
• Mason Nakamura, Justin Svegliato, Samer B Nashed, Shlomo Zilberstein, and Stuart Russell, Formal Composition of Robotic Systems as Contract Programs. In Proc. IROS-23, 2023.
• Luke Bailey, Euan Ong, Stuart Russell, and Scott Emmons, Image Hijacks: Adversarial Images can Control Generative Models at Runtime, arXiv:2309.00236, September 2023.
• Dylan Cope, Justin Svegliato, and Stuart Russell, Learning to plan with tree search via deep RL. In Proc. IJCAI-23 Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning, 2023.
• Alistair Knott, Dino Pedreschi, Raja Chatila, Tapabrata Chakraborti, Susan Leavy, Ricardo Baeza-Yates, David Eyers, Andrew Trotman, Paul D. Teal, Przemyslaw Biecek, Stuart Russell, and Yoshua Bengio, Generative AI models should include detection mechanisms as a condition for public release. Ethics and Information Technology, 25, 2023. (prepublication version)
• Stuart Russell and Peter Norvig, Künstliche Intelligenz: Ein moderner Ansatz (4th Edition). (German translation of Artificial Intelligence: A Modern Approach, fourth edition.) Munich: Verlag Pearson Studium, 2023.
• Stuart Russell, Human Compatible (revised edition). London: Penguin, 2023.
• Alistair Knott, Dino Pedreschi, Raja Chatila, Susan Leavy, Ricardo Baeza-Yates, Tapabrata Chakraborti, David Eyers, Andrew Trotman, Lama Saouma, Virginia Morini, Valentina Pansanella, Paul D. Teal, Przemyslaw Biecek, Ivan Bratko, Stuart Russell, and Yoshua Bengio, State-of-the-art Foundation AI Models Should be Accompanied by Detection Mechanisms as a Condition of Public Release, Report, Global Partnership on Artificial Intelligence, 2023.
• Stuart Russell, Opening statement for the hearing on Oversight of AI: Principles for Regulation, U.S. Senate Committee on the Judiciary, Subcommittee on Privacy, Technology, and the Law, Washington, DC, July 25, 2023.
• Stuart Russell, Written testimony for the hearing on Oversight of AI: Principles for Regulation, U.S. Senate Committee on the Judiciary, Subcommittee on Privacy, Technology, and the Law, Washington, DC, July 25, 2023.
• Cassidy Laidlaw, Stuart Russell, and Anca Dragan, Bridging RL Theory and Practice with the Effective Horizon, ICML 2023 Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023. (Best Paper Award)
• Joar Skalse, Matthew Farrugia-Roberts, Stuart Russell, Alessandro Abate, and Adam Gleave, Invariance in policy optimisation and partial identifiability in reward learning. In Proc. ICML-23, 2023.
• Tony Tong Wang, Adam Gleave, Tom Tseng, Nora Belrose, Kellin Pelrine, Joseph Miller, Michael D Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, and Stuart Russell, Adversarial policies beat superhuman Go AIs. In Proc. ICML-23, 2023.
• Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael D Dennis, Stuart Russell, Who needs to know? Minimal knowledge for optimal coordination. In Proc. ICML-23, 2023.
• Stuart Russell, Corrected oral evidence: Artificial intelligence in weapons systems, Artificial Intelligence in Weapons Systems Committee, House of Lords, London, June 15, 2023.
• Andrew Critch and Stuart Russell, TASRA: A Taxonomy and Analysis of Societal-Scale Risks from AI, arXiv:2306.06924, June 2023
• Stuart Russell, How can humans maintain control over AI, forever?, Boston Globe, May 15, 2023.
• Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, and Jiantao Jiao, Optimal conservative offline RL with general function approximation via augmented Lagrangian. In Proc. ICLR-23, 2023.
• Stuart Russell, AI has much to offer humanity. It could also wreak terrible harm. It must be controlled.. The Guardian, April 2, 2023.
• Peter Barnett, Rachel Freedman, Justin Svegliato, and Stuart Russell, Active Reward Learning from Multiple Teachers. arXiv:2303.00894, March 2023.
• Yoshua Bengio, Stuart Russell, Elon Musk, Steve Wozniak, and Yuval Noah Harari, Pause giant AI experiments: An open letter. Future of Life Institute, March 2023.
• Tony T. Wang, Adam Gleave, Tom Tseng, Nora Belrose, Kellin Pelrine, Joseph Miller, Michael D Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell, Adversarial policies beat superhuman Go AIs. arXiv:2211.00241, February 2023.
• Alexander Lew, George Matheos, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, and Vikash Mansinghka, SMCP3: SMC with Probabilistic Program Proposals. In Proc. Twenty-Sixth International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 2023.
• Stuart Russell, AI weapons: Russia's war in Ukraine shows why the world must enact a ban. Nature, 614, 620-623, 2023. (21 February, 2023)

• Tony Tong Wang, Adam Gleave, Nora Belrose, Tom Tseng, Michael D Dennis, Yawen Duan, Viktor Pogrebniak, Joseph Miller, Sergey Levine, and Stuart Russell, Adversarial policies beat superhuman Go AIs. In Proc. NeurIPS-22 Workshop on Deep Reinforcement Learning, 2022.
• Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, and Stuart Russell, imitation: Clean Imitation Learning Implementations. arxiv.org:2211.11972, November 2022.
• Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, and Jiantao Jiao, Optimal conservative offline RL with general function approximation via augmented Lagrangian. arXiv:2211.00716, November 2022.
• Stuart Russell, Politicians must prepare for AI or face the consequences. The House (magazine of the UK Houses of Parliament), Oct 14, 2022.
• Samer B. Nashed, Justin Svegliato, Abhinav Bhatia, Stuart Russell, and Shlomo Zilberstein, Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning. In Proc. IROS-22, 2022.
• Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, and Stuart Russell, Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. IEEE Transactions on Information Theory, 68 (12), 8156-8196, 2022.
• Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer, and Stuart Russell, For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. In Proc. ICML-22, 2022.
• Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, and Anca Dragan, Estimating and Penalizing Induced Preference Shifts in Recommender Systems. In Proc. ICML-22, 2022.
• Andrew Critch, Michael Dennis, and Stuart Russell, Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory. arXiv:2208.07006, August 2022.
• Stuart Russell and Peter Norvig, Inteligencia Artificial: Uma Abordagem Moderna. (Portuguese translation of Artificial Intelligence: A Modern Approach, fourth edition.) Translated by Daniel Vieira and Flavio Soares Correa da Silva. Rio de Janeiro: GEN LTC, 2022.
• Kenji Doya, Arisa Ema, Hiroaki Kitano, Masamichi Sakagami, and Stuart Russell, Social impact and governance of AI and neurotechnologies. Neural Networks, 152, 542-554, 2022.
• Stuart Russell, Why we need to regulate non-state use of arms. Global Agenda, World Economic Forum, 18 May 2022.
• Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H Wang, Ping Luo, Stuart Russell, Pieter Abbeel, and Rohin Shah, An empirical investigation of representation learning for imitation. arXiv:2205.07886, May 2022.
• Stuart Russell, Banning Lethal Autonomous Weapons: An Education. Issues in Science and Technology, XXXVIII(3), 60-65, 2022.
• Stuart Russell, If we succeed. Daedalus, Spring 2022, 43-57.
• Stuart Russell and Peter Norvig, Intelligenza Artificiale 4/Ed. Vol. 2 - Un Approccio Moderno. (Vol. 2 of Italian translation of Artificial Intelligence: A Modern Approach, fourth edition.) Translated by Stefano Gaburri and Francesco Amigoni. Rome: Pearson Italia, 2022.
• Stuart Russell, Provably beneficial artificial intelligence (abstract). In Proc. IUI-22, 2022.
• Stuart Russell, Biography of Judea Pearl. In Hector Geffner, Rina Dechter, Joseph Y. Halpern (eds.), Probabilistic and Causal Inference: The Works of Judea Pearl, ACM Press, 2022.
• Arnaud Fickinger, Samuel Cohen, Stuart Russell, and Brandon Amos, Cross-Domain Imitation Learning via Optimal Transport. In Proc. ICLR-22, 2022.
• Stephen Casper, Shlomi Hod, Daniel Filan, Cody Wild, Andrew Critch, and Stuart Russell, Graphical clusterability and local specialization in deep neural networks. In Proc. ICLR-22 Workshop on Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data, 2022.
• Cynthia Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven Wang, Ping Luo, Stuart Russell, Pieter Abbeel, and Rohin Shah, An Empirical Investigation of Representation Learning for Imitation. In Advances in Neural Information Processing Systems 34, 2022. (Proceedings of NeurIPS-21, Datasets and Benchmarks.)
• Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, and Stuart Russell, MADE: Exploration via Maximizing Deviation from Explored Regions . In Advances in Neural Information Processing Systems 34, 2022. (Proceedings of NeurIPS-21.)
• Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, and Stuart Russell, Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. In Advances in Neural Information Processing Systems 34, 2022. (Proceedings of NeurIPS-21.)
• Cassidy Laidlaw and Stuart Russell, Uncertain Decisions Facilitate Better Preference Learning. In Advances in Neural Information Processing Systems 34, 2022. (Proceedings of NeurIPS-21.)
• Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart Russell, and Noam Brown, Scalable Online Planning via Reinforcement Learning Fine-Tuning. In Advances in Neural Information Processing Systems 34, 2022. (Proceedings of NeurIPS-21.)
• Stuart Russell and Peter Norvig, Intelligence artificielle, 4e éd.. (French translation of Artificial Intelligence: A Modern Approach, fourth edition.) Paris: Pearson Education France, 2022.
• Stuart Russell, Kao čovjek: Umjetna inteligencija - napredak ili prijetnja?. (Croatian translation of Human Compatible.) Translated by Vinko Zgaga. Zagreb, Croatia: Planetopija, 2022.

• Stuart Russell, Inteligência Artificial a Nosso Favor: como manter o controle sobre a tecnologia. (Portuguese translation of Human Compatible.) Translated by Berila Vargas and illustrated by Mateus Valadares. São Paulo, Brazil: Companhia das Letras, 2021.
• Stuart Russell, Jako člověk: Umělá inteligence a problém jejího ovládání. (Czech translation of Human Compatible.) Translated by Jiří Zlatuška. Prague, Czechia: Dokořán, 2021.
• Stuart Russell and Daniel Susskind (Eds.), Positive AI Economic Futures, Insight Report, World Economic Forum, November 22, 2021.
• Shlomi Hod, Daniel Filan, Stephen Casper, Andrew Critch, and Stuart Russell, Quantifying local specialization in deep neural networks. arXiv:2110.08058, October 2021.
• Arnaud Fickinger, Samuel Cohen, Stuart Russell, and Brandon Amos,, Cross-Domain Imitation Learning via Optimal Transport. arXiv:2110.03684, October 2021.
• Alexander Bustamante, Brandie M. Nonnecke, and Stuart Russell (Eds.), Responsible Artificial Intelligence: Recommendations to Guide the University of California's Artificial Intelligence Strategy. Final report of the University of California Presidential Working Group on AI. October 2021.
• Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, and Anca Dragan, Estimating and Penalizing Induced Preference Shifts in Recommender Systems. In Proc. 15th ACM Conference on Recommender Systems, 2021.
• Stuart Russell and Peter Norvig, Intelligenza Artificiale 4/Ed. Vol. 1 - Un Approccio Moderno. (Vol. 1 of Italian translation of Artificial Intelligence: A Modern Approach, fourth edition.) Translated by Stefano Gaburri and Francesco Amigoni. Rome: Pearson Italia, 2021.
• Stuart Russell, It's time to ban autonomous killer robots before they become a threat, Financial Times, August 5, 2021.
• Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, and Sergey Levine, Explore and control with adversarial surprise. arXiv:2107.07394, July 2021.
• Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, and Sergey Levine, Explore and control with adversarial surprise. In Proc. ICML-21 Workshop on Unsupervised Reinforcement Learning, 2021.
• Stuart Russell, The history and future of AI, Oxford Review of Economic Policy, 37(3), 509-520, 2021.
• Stuart Russell, Συμβατή με τον άνθρωπο. (Greek translation of Human Compatible.) Athens: Travlos Publications.
• Stuart Russell, Artificial Intelligence and the Problem of Control. In H. Werthner, E. Prem, E. A. Lee, and C. Ghezzi (eds), Perspectives on Digital Humanism, Springer, 2021.
• Stuart Russell, İnsanlık için Yapay Zekâ: Yapay Zekâ ve Kontrol Problemi. (Turkish translation of Human Compatible.) Translated by Barış Satılmış. Ankara: Buzdağı Yayınevi, 2021.
• Stuart Russell, 어떻게 인간과 공존하는 인공지능을 만들 것인가. (Korean translation of Human Compatible.) Translated by Lee Han-eum. Seoul: Gimm-Young, 2021.
• Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, and Anca Dragan, The MineRL BASALT Competition on Learning from Human Feedback. arxiv.org/abs/2107.01969, July 2021.
• Stuart Russell, Anthony Aguirre, Emilia Javorsky and Max Tegmark, Lethal Autonomous Weapons Exist; They Must Be Banned, IEEE Spectrum, June 16, 2021.
• Cassidy Laidlaw and Stuart Russell, Learning the preferences of uncertain humans with inverse decision theory. arXiv:2106.10394, June 2021.
• Stuart Russell, AI新生. (Japanese translation of Human Compatible.) Translated by Nobuhiko Matsui. Tokyo: Misuzu Shobo, 2021.
• Charlotte Roman, Michael Dennis, Andrew Critch, and Stuart Russell. Accumulating Risk Capital Through Investing in Cooperation. In Proc. AAMAS-21.
• Scott Emmons, Caspar Oesterheld, Andrew Critch, Vince Conitzer, and Stuart Russell, Symmetry, equilibria, and robustness in common-payoff games. In Proc. AAMAS-21 Workshop on Games, Agents, and Incentives, 2021.
• Raja Chatila, Virginia Dignum, Michael Fisher, Fosca Gianotti, Katharina Morik, Stuart Russell, David Sadek, and Karen Yeung, ``Trustworthy AI.'' In Bertrand Braunschweig and Malik Ghallab (eds.), Reflections on Artificial Intelligence for Humanity, Springer, 2021.
• Jocelyn Maclure and Stuart Russell, ``AI for Humanity: The Global Challenges.'' In Bertrand Braunschweig and Malik Ghallab (eds.), Reflections on Artificial Intelligence for Humanity, Springer, 2021.
• George Matheos, Alexander K. Lew, Matin Ghavamizadeh, Stuart Russell, Marco Cusumano-Towner, Vikash K. Mansinghka, ``Transforming Worlds: Automated Involutive MCMC for Open-Universe Probabilistic Models.'' In Proc. 3rd Symposium on Advances in Approximate Bayesian Inference (AABI), 2021.
• Stuart Russell, ``Human-Compatible Artificial Intelligence.'' In Stephen Muggleton and Nick Chater (eds.), Human-Like Machine Intelligence, Oxford University Press, 2021.
• Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell and Jan Leike, ``Quantifying Differences in Reward Functions.'' In Proc. ICLR-21, 2021.
• Daniel Filan, Stephen Casper, Shlomi Hod, Cody Wild, Andrew Critch, and Stuart Russell, Clusterability in neural networks. arXiv:, March 2021.
• Prasad Tadepalli and Stuart Russell, PAC-Learning of Causal Trees with Latent Variables. In Proc. AAAI-21, 2021.
• Paria Rashidinejad, Jiantao Jiao, and Stuart Russell, ``SLIP: Learning to predict in unknown dynamical systems with long-term memory.'' In Advances in Neural Information Processing Systems 33, 2021. (Proceedings of NeurIPS-20.)
• Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, and Sergey Levine, ``Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design.'' In Advances in Neural Information Processing Systems 33, 2021. (Proceedings of NeurIPS-20.)
• Sam Toyer, Rohin Shah, Andrew Critch, and Stuart Russell, ``The MAGICAL Benchmark for Robust Imitation.'' In Advances in Neural Information Processing Systems 33, 2021. (Proceedings of NeurIPS-20.)

• Stuart Russell, Совместимость: Как контролировать искусственный интеллект. (Russian translation of Human Compatible.) Moscow: Alpina, 2020.
• Stuart Russell, Сумісний з людиною. Штучний інтелект і проблема контролю, (Ukrainian translation of Human Compatible.) Translated by Viktoria Zenhyea. Kiev: Bookchef, 2020.
• Stuart Russell, AI新生. (Chinese translation of Human Compatible.) Translated by Zhang Yi. Beijing: CITIC Press, 2020.
• Thanard Kurutach, Julia Peng, Yang Gao, Stuart Russell, and Pieter Abbeel, Discrete Predictive Representation for Long-Horizon Planning. In Proc. NeurIPS-20 Workshop on Object Representations for Learning and Reasoning, 2020.
• Rohin Shah, Pedro Freire, Neel Alex, Rachel Freedman, Dmitrii Krasheninnikov, Lawrence Chan, Michael Dennis, Pieter Abbeel, Anca Dragan and Stuart Russell, ``Benefits of Assistance over Reward Learning. In Proc. NeurIPS-20 Workshop on Cooperative AI. (Best Paper Prize)
• Arnaud Fickinger, Simon Zhuang, Andrew Critch, Dylan Hadfield-Menell and Stuart Russell, ``Multi-Principal Assistance Games: Definition and Collegial Mechanisms. In Proc. NeurIPS-20 Workshop on Cooperative AI, 2020
• Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell and Jan Leike, ``Quantifying Differences in Reward Functions. In Proc. NeurIPS-20 Workshop on Deep Reinforcement Learning.
• Pedro Freire, Adam Gleave, Sam Toyer and Stuart Russell, ``DERAIL: Diagnostic Environments for Reward And Imitation Learning. In Proc. NeurIPS-20 Workshop on Deep Reinforcement Learning, 2020.
• Eric Michaud, Adam Gleave, and Stuart Russell, ``Understanding learned reward functions. In Proc. NeurIPS-20 Workshop on Deep Reinforcement Learning, 2020.
• Eric J Michaud, Adam Gleave, and Stuart Russell, Understanding learned reward functions. arXiv:2012.05862, December 2020.
• Paria Rashidinejad, Xiao Hu, and Stuart Russell, Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach.'' Physiological Measurement, 41(10), 104003.
• Stuart Russell and Charles-Édouard Bouée, ``The secret to designing a positive future with AI? Imagination.'' World Economic Forum, October 30, 2020.
• Stuart Russell, ``Artificial intelligence: A binary approach.'' In S. Matthew Liao (Ed.), Ethics of Artificial Intelligence. Oxford: Oxford University Press, 2020.
• Stuart Russell, Human Compatible: Künstliche Intelligenz und wie der Mensch die Kontrolle ber superintelligente Maschinen behält. (German translation of Human Compatible.) Translated by Guido Lenz. Cologne: mitp Verlag, 2020.
• Stuart Russell, Die gar nicht mal so grosse KI-Debatte, Digitale Welt, September 4, 2020.
• Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, and Jan Leike, ``Quantifying Differences in Reward Functions. arXiv:2006.13900, June 2020.
• Ronan Le Bras, Nimar Arora, Noriyuki Kushida, Pierrick Mialle, Istvan Bondar, Elena Tomuta, Fekadu Kebede Alamneh, Paulino Feitio, Marcela Villarroel, Beatriz Vera, Alexander Sudakov, Shaban Laban, Stuart Nippress, David Bowers, Stuart Russell, and Tammy Taylor, ``NET-VISA from Cradle to Adulthood. A Machine-Learning Tool for Seismo-Acoustic Automatic Association,'' Pure and Applied Geophysics, 178, 2437-2458, 2020.
• Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch, and Stuart Russell, ``Pruned Neural Networks are Surprisingly Modular,'' arXiv:2003.04881, March 2020.
• Stuart Russell and Peter Norvig, ``Artificial Intelligence: A Modern Approach.'' 4th Edition, Prentice Hall, 2020.
• Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine and Stuart Russell, ``Adversarial Policies: Attacking Deep Reinforcement Learning.'' In Proc. ICLR-20, Addis Ababa, 2020.

• Stuart Russell, Human Compatible: AI and the Problem of Control . New York: Viking, 2019.
• Olaf Groth, Mark Nitzberg, and Stuart Russell, AI algorithms need FDA-style drug trials, Wired, August 15, 2019.
• Ronald Arkin, Leslie Kaelbling, Stuart Russell, Dorsa Sadigh, Paul Scharre, Bart Selman, and Toby Walsh, A Path Towards Reasonable Autonomous Weapons Regulation, IEEE Spectrum, October, 2019.
• Stuart Russell, Many Experts Say We Shouldn't Worry About Superintelligent AI. They're Wrong, IEEE Spectrum, October, 2019.
• Stuart Russell, How to Stop Superhuman A.I. Before It Stops Us, New York Times, October 8, 2019.
• Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, and Yuandong Tian, ``Bayesian Relational Memory for Semantic Visual Navigation.'' In Proc. ICCV-19, Seoul, 2019.
• R. Le Bras, N. Arora, N. Kushida, P. Mialle, I. Bondar, S. Laban, M. Villarroel, B. Vera, A. Sudakov, S. Nippress, D. Bowers, S. Russell, and T. Taylor, ``The Machine-Learning Tool NET-VISA from Cradle to Adulthood - The Next Generation System of the IDC and the SnT Process.'' In CTBT: Science and Technology Conference, Vienna, 2019.
• N. Arora, S. Russell, P. Mialle, R. Le Bras, and P. Nielsen, ``Recent Advances and Status of Generative Modeling for Network Processing at the CTBTO.'' In CTBT: Science and Technology Conference, Vienna, 2019.
• Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine and Stuart Russell, ``Adversarial Policies: Attacking Deep Reinforcement Learning.'' In Proc. ICML-19 Workshop on Security and Privacy in Machine Learning, Long Beach, California, 2019. Also arXiv:1905.10615.
• Prasad Tadepalli, Cameron Barrie, and Stuart J. Russell, ``Learning Causal Trees with Latent Variables via Controlled Experimentation.'' In Proc. AAAI Spring Symposium on Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-Based AI, Stanford, 2019.
• Joshua Peterson, David Bourgin, Daniel Reichman, Thomas Griffiths, and Stuart Russell, ``Cognitive model priors for predicting human decisions.'' In Proc. ICML-19, Long Beach, California, 2019. (See also video of presentation.)
• Stuart Russell, ``The Purpose Put Into the Machine.'' In John Brockman, Ed., Possible Minds: 25 Ways of Looking at AI, Penguin Press, 2019.
• Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang, and Stuart Russell, ``Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient.'' In Proc. AAAI-19, Honolulu, 2019.

• Aaron Tucker, Adam Gleave, and Stuart Russell, ``Inverse Reinforcement Learning for Video Games.'' In Proc. NeurIPS-18 Workshop on Deep RL, 2018.
• Stuart Russell, ``How to make AI that works, for us, BBC Science Focus, November 16, 2018.
• Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, and Pieter Abbeel, ``Learning Plannable Representations with Causal InfoGAN.'' In Proc. NeurIPS-18, Montreal, 2018.
• Tongzhou Wang, Yi Wu, David Moore, and Stuart Russell, ``Meta-Learning MCMC Proposals.'' In Proc. NeurIPS-18, Montreal, 2018.
• Nishant Desai, Andrew Critch, and Stuart Russell, ``Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making.'' In Proc. NeurIPS-18, Montreal, 2018.
• Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell and Pieter Abbeel, ``Learning Plannable Representations with Causal InfoGAN.'' In Proc. ICML / IJCAI / AAMAS 2018 Workshop on Planning and Learning (PAL-18), Stockholm, 2018. Revised version on arXiv:1807.09341.
• Nicholas Hay, Siddharth Srivastava, Yi Wu, and Stuart Russell, ``Discrete-Continuous Mixtures in Probabilistic Programming: Extended Semantics and General Inference Algorithms.'' In Proc. ICML-18, Stockholm, 2018.
• Dhruv Malik, Malayandi Palaniappan, Jaime Fisac, Dylan Hadfield-Menell, Stuart Russell, and Anca Dragan, ``An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning.'' In Proc. ICML-18, Stockholm, 2018.
• Stuart Russell, ``The new weapons of mass destruction?,'' Security Times, February 2018, 40-41. (Special issue of The German Times for the 54th Munich Security Conference.)
• Stuart Russell, Anthony Aguirre, Ariel Conn, and Max Tegmark, ``Why You Should Fear 'Slaughterbots' -- A Response [to Scharre].'' IEEE Spectrum, January 23, 2018.

• Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart Russell, Anca Dragan, ``Inverse Reward Design.'' In Proc. NeurIPS-17, Long Beach, California, 2017.
• Andrew Critch and Stuart Russell, ``Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-making,'' arXiv:1711.00363, October 2017.
• Stuart Russell, ``Artificial intelligence: The future is superintelligent.'' (Review of Life 3.0 by Max Tegmark.) Nature, 548, 520-521, 2017. (31 August 2017)
• Slaughterbots, short film. Released Nov 13, 2017.
• Yi Wu, David Bamman, and Stuart Russell, ``Adversarial Training for Relation Extraction,'' In Proc. EMNLP-17, Copenhagen, 2017.
• Tongzhou Wang, Yi Wu, David A. Moore, Stuart J. Russell, ``Neural Block Sampling,'' arXiv:1708.06040v1, August 2017.
• Smitha Milli, Dylan Hadfield-Menell, Anca Dragan, and Stuart Russell, ``Should Robots be Obedient?.'' In Proc. IJCAI-17, Melbourne, 2017. Also on arXiv.
• Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, and Stuart Russell, ``The off-switch game.'' In Proc. IJCAI-17, Melbourne, 2017.
• Aijun Bai and Stuart Russell, ``Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions.'' In Proc. IJCAI-17, Melbourne, 2017.
• Malayandi Palaniappan, Dhruv Malik, Dylan Hadfield-Menell, Anca Dragan, Stuart Russell, ``Efficient Cooperative Inverse Reinforcement Learning.'' In Proc. ICML Workshop on Reliable Machine Learning in the Wild, 2017.
• David Moore and Stuart Russell, ``Signal-Based Bayesian Seismic Monitoring.'' In Proc. Twentieth International Conference on Artificial Intelligence and Statistics, Fort Lauderdale, Florida, 2017.
• Aijun Bai and Stuart Russell, ``Speeding up HAM learning with internal transitions.'' In Proc. Third Multidisciplinary Conference on Reinforcement Learning and Decision Making, Ann Arbor, Michigan, 2017.
• Yusuf B. Erol, Yi Wu, Lei Li, and Stuart Russell, A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models. In Proc. AAAI-17, San Francisco, 2017.
• Stuart Russell, Provably beneficial artificial intelligence. In The Next Step: Exponential Life, BBVA OpenMind, 2017.

• Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, and Stuart Russell, Cooperative Inverse Reinforcement Learning. In Proc. NeurIPS-16, Barcelona, 2016.
• Hugh Chen, Yusuf Erol, Eric Shen, and Stuart Russell, Probabilistic model-based approach for heart beat detection.'' Physiological Measurement, 37(9), 1404-1421.
• Stuart Russell, Nimar S. Arora, and David Moore, ``Bayesian Monitoring Systems for the CTBT: Historical Development and New Results.'' Eos Transactions of the American Geophysical Union, Fall Meeting Supplement, Abstract S34A-07, 2016.
• David Moore and Stuart Russell, ``Initial Evaluation of Signal-Based Bayesian Monitoring.'' Eos Transactions of the American Geophysical Union, Fall Meeting Supplement, Abstract S31A-2707, 2016.
• Nimar S. Arora and Stuart Russell, ``Fine-Scale Event Location and Error Analysis in NET-VISA.'' Eos Transactions of the American Geophysical Union, Fall Meeting Supplement, Abstract S31A-2710, 2016.
• Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, and Stuart Russell, The Off-Switch Game, arXiv:1611.08219, November 2016.
• Stuart Russell, Tiptoe through the nuclear minefield, in Nature, November 11, 2016.
• Allan Dafoe and Stuart Russell, Yes, We Are Worried About the Existential Risk of Artificial Intelligence. MIT Technology Review, Nov 2, 2016.
• Dylan Hadfield-Menell, Christopher Lin, Rohan Chitnis, Stuart Russell, and Pieter Abbeel, Sequential Quadratic Programming for Task Plan Optimization, In Proc. IROS-16, Daejeon, Korea, 2016.
• Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, and Stuart Russell, Cooperative Inverse Reinforcement Learning, arXiv:1606.03137, June 2016.
• Stuart Russell, Should we fear supersmart robots?. In Scientific American, 314, 58-59, June 2016.
• Aijun Bai, Siddharth Srivastava, and Stuart Russell, Markovian State and Action Abstractions via Hierarchical MCTS. In Proc. IJCAI-16, New York, 2016.
• Yi Wu, Lei Li, and Stuart Russell, Swift: Compiled Inference for Probabilistic Programming Languages. In Proc. IJCAI-16, New York, 2016.
• Stuart Russell, Ole Torp Lassen, Justin Uang, and Wei Wang, The Physics of Text: Ontological Realism in Information Extraction. In Proceedings of the NAACL Workshop on Automated Knowledge Base Construction (AKBC), San Diego, 2016.
• Siddharth Srivastava, Stuart Russell, and Alessandro Pinto, Metaphysics of Planning Domain Descriptions. In Proc. AAAI-16, Phoenix, 2016.
• Stuart Russell, Robots in war: the next weapons of mass destruction?, World Economic Forum, January 17, 2016.
• Stuart Russell and Peter Norvig, 인공지능 : 현대적 접근방식(제 3판), Volumes 1 and 2 (Korean translation of Artificial Intelligence: A Modern Approach, third edition.) Seoul: J-pub Co., 2016.
• Stuart Russell and Peter Norvig, Жасанды интеллект: Жаңашыл әдіс (Kazakh translation of Artificial Intelligence: A Modern Approach, third edition.) Translated by M. E. Mansurova, K. S. Duisebekova, and S. Z. Sapakova. Almaty, Kazakhstan: Association of Higher Education Institutions of the Republic of Kazakhstan, 2013, 2014, 2016.

• *Hugh Chen, Yusuf Erol, Eric Shen, Stuart Russell, Probabilistic Model-Based Approach for Heart Beat Detection. arXiv:1512.07931, December 2015.
• David A. Moore, Kevin Mayeda, Stephen C. Myers, Stuart J. Russell, Bayesian Inference for Signal-Based Seismic Monitoring (poster), AGU Fall Meeting, San Francisco, 2015.
• Eric Eaton, Tom Dietterich, Maria Gini, Barbara J. Grosz, Charles L. Isbell, Subbarao Kambhampati, Michael Littman, Francesca Rossi, Stuart Russell, Peter Stone, Toby Walsh, and Michael Wooldridge, Who speaks for AI?, AI Matters, Volume 2 Issue 2, December 2015, Pages 4-14.
• Stuart Russell, Tom Dietterich, Eric Horvitz, Bart Selman, Francesca Rossi, Demis Hassabis, Shane Legg, Mustafa Suleyman, Dileep George, and Scott Phoenix, Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter, AI Magazine, Vol. 36, No. 4, 2015.
• Stuart Russell, Daniel Dewey, and Max Tegmark, Research Priorities for Robust and Beneficial Artificial Intelligence, AI Magazine, Vol. 36, No. 4, 2015. Also available on arXiv.
• Stuart Russell, Moral Philosophy Will Become Part of the Tech Industry, Time, September 15, 2015.
• Stuart Russell, Hiroshima et Nagasaki: Des leçons pour le présent et pour l'avenir, Le Monde, August 7, 2015.
• Stuart Russell, Ban lethal autonomous weapons, Boston Globe, September 8, 2015.
• David Moore and Stuart Russell, Gaussian Process Random Fields. In Proc. NeurIPS-15, 2015.
• Stuart Russell, Max Tegmark, and Toby Walsh, Why we really should ban autonomous weapons: A response [to Wallace], Kurzweil AI Blog, August 10, 2015.
• Stuart Russell, Max Tegmark, and Toby Walsh, Why We Really Should Ban Autonomous Weapons: A Response [to Ackerman], IEEE Spectrum, August 3, 2015.
• Dylan Hadfield-Menell and Stuart Russell, Multitasking: Efficient Optimal Planning for Bandit Superprocesses. In Proc. UAI-15, 2015.
• Wei Wang and Stuart Russell, A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC. In Proc. UAI-15, 2015.
• *Yusuf Erol, Romi Phadte, Sammy Sidhu, Claire Asselstine, David Phillips, and Stuart Russell, Model-Based Probabilistic Inference for Intensive Care Medicine. In Proc. Fifth Conference on Meaningful Use of Complex Medical Data, Los Angeles, 2015.
• Stuart Russell, Unifying logic and probability. Communications of the ACM, 58(7), 88-97, 2015.
  • See also the prepublication version and accompanying video created by Christopher Schodt for CACM.
• Lei Li, Yi Wu and Stuart J. Russell, SWIFT: Compiled Inference for Probabilistic Programs. Technical Report EECS-2015-12, UC Berkeley, 2015.
• Stuart Russell, Take a stand on AI weapons. Nature, 521(7553), May 28, 2015.
• Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell, Tractability of Planning with Loops. In Proc. AAAI-15, Austin, Texas, 2015.
• F. Lieder, D. Plunkett, J. Hamrick, S. Russell, N. Hay, T. Griffiths, Algorithm selection by rational metareasoning as a model of human strategy selection. In Advances in Neural Information Processing Systems 23, MIT Press, 2015.
• Stuart Russell, Will they make us better people?, contribution to the Annual Question, 2015 on edge.org. Also in John Brockman, Ed., What to Think About Machines That Think, Harper Collins, 2015.

• Stuart Russell, Of Myths and Moonshine, contribution to the conversation on The Myth of AI on edge.org, November 2014.
• Stuart Russell, White paper: Value alignment in autonomous systems, November 1, 2014.
• Stephen Hawking, Stuart Russell, Max Tegmark, and Frank Wilczek, ``Transcending Complacency on Superintelligent Machines.'' Huffington Post, April 19, 2014.
• Stuart Russell, Transcendence: An AI Researcher Enjoys Watching His Own Execution, Huffington Post, April 29, 2014.
• Stuart Russell, ``Rationality and Intelligence: A Brief Update.'' In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence (Synthese Library). Berlin: Springer, 2014.
• Stuart Russell, ``Unifying Logic and Probability: A New Dawn for AI?'' In Proc. IPMU-14, Montpellier, France, 2014.
• Siddharth Srivastava, Stuart Russell, and Paul Ruan, ``First-Order Open-Universe POMDPs.'' In Proc. UAI-14, Quebec City, Canada, 2014.
• David Moore and Stuart Russell, ``Fast Gaussian Process Posteriors with Product Trees.'' In Proc. UAI-14, Quebec City, Canada, 2014.
• Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell, and Pieter Abbeel, ``Combined Task and Motion Planning Through an Extensible Planner-Independent Interface Layer.'' In Proc. ICRA-14, Hong Kong, 2014.
• Mark Rogers, Lei Li, and Stuart Russell, ``Multilinear Dynamical Systems for Tensor Time Series.'' In Advances in Neural Information Processing Systems 23, MIT Press, 2014.

• *Yusuf B. Erol, Stuart J. Russell, Ahilan Sivaganesan, and Geoffrey T. Manley, ``Combined State and Parameter Estimation of Human Intracranial Hemodynamics.'' In Proc. NeurIPS-13 Workshop on Machine Learning for Clinical Data Analysis and Healthcare, Lake Tahoe, California, 2013
• Siddharth Srivastava, Xiang Cheng, Stuart J. Russell and Avi Pfeffer, ``First-Order Open-Universe POMDPs: Formulation and Algorithms.'' Technical Report No. UCB/2013-243, EECS Department, University of California, Berkeley, 2013.
• Sharad Vikram, Lei Li, and Stuart J. Russell, ``Writing and sketching in the air, recognizing and controlling on the fly.'' In CHI Extended Abstracts, Paris, 2013.
• Yusuf B. Erol, Lei Li, Bharath Ramsundar, and Stuart Russell, ``The Extended Parameter Filter.'' In Proc. Thirtieth International Conference on Machine Learning, Atlanta, 2013.
• Siddharth Srivastava, Lorenzo Riano, Stuart Russell, and Pieter Abbeel, ``Using Classical Planners for Tasks with Continuous Operators in Robotics.'' In ICAPS-13 Workshop on Planning and Robotics, Rome, 2013.
• Nimar S. Arora, Stuart Russell, and Erik Sudderth, ``NET-VISA: Network Processing Vertically Integrated Seismic Analysis.'' In Bulletin of the Seismological Society of America, 103(2A), 709-729, 2013.
• Lei Li, Bharath Ramsundar, and Stuart Russell, ``Dynamic Scaled Sampling for Deterministic Constraints.'' In Proc. Sixteenth International Conference on Artificial Intelligence and Statistics, Scottsdale, Arizona, 2013.
• Stuart Russell and Peter Norvig, 《人工智能——一种现代方法(第三版)》 (Chinese Simplified translation of Artificial Intelligence: A Modern Approach, third edition.) Tsinghua University Press, 2013.

• Stuart Russell and Peter Norvig, Künstliche Intelligenz: Ein moderner Ansatz (3rd Edition). (German translation of Artificial Intelligence: A Modern Approach, third edition.) Munich: Verlag Pearson Studium, 2012.
• David A. Moore, Kevin Mayeda, Steve Myers, Min Joon Seo, and Stuart Russell, ``Progress in Signal-Based Bayesian Monitoring.'' In Proc. Monitoring Research Review (MRR 2012), Albuquerque, New Mexico, 2012.
• Nimar S. Arora, Jeffrey Given, Elena Tomuta, Stuart Russell, and Spilios Spiliopoulos, ``Analyst Evaluation of NET-VISA (Network Processing Vertically Integrated Seismic Analysis) at the CTBTO.'' In Proc. Monitoring Research Review (MRR 2012), Albuquerque, New Mexico, 2012.
• Shaunak Chatterjee and Stuart Russell, ``Uncertain observation times.'' In Proc. 6th International Conference on Scalable Uncertainty Management (SUM-12), Marburg, Germany, 2012.
• Nicholas Hay, Stuart Russell, Solomon Eyal Shimony, and David Tolpin, ``Selecting Computations: Theory and Applications.'' In Proc. UAI-12, Catalina Island, 2012.
• Siddharth Srivastava and Stuart Russell, ``First-Order Models for POMDPs.'' In Proc. 2nd International Workshop on Statistical Relational AI (StarAI-12), Catalina Island, 2012.
• Nimar Arora and Stuart Russell, ``A model of seismic coda arrivals to suppress spurious events (abstract).'' In Proc. European Geophysical Union General Assembly, Vienna, 2012.
• Ahilan Sivaganesan, Yusuf Erol, Geoffrey Manley, and Stuart Russell, ``Modeling and Machine Learning of Cerebrovascular Dynamics: A Framework for Monitoring Unmeasurable Patient Variables.'' Neurosurgery, 71(2), E559, 2012.
• Ahilan Sivaganesan, Yusuf Erol, Geoffrey Manley, and Stuart Russell, ``Modeling and Machine Learning of Cerebrovascular Dynamics: A Framework for Monitoring Unmeasurable Patient Variables (abstract).'' Congress of Neurological Surgeons Annual Meeting, Chicago, 2012.

• Nimar Arora, Tony Dear, and Stuart Russell, ``Scalable Probabilistic Inference for Global Seismic Monitoring.'' Eos Transactions of the American Geophysical Union, 92(53), Fall Meeting Supplement, Abstract S43B-2238, 2011.
• Emma Brunskill and Stuart Russell, ``Partially observable sequential decision making for problem selection in an intelligent tutoring system.'' In Proc. International Conference on Educational Data Mining (EDM), 2011.
• Nicholas J. Hay and Stuart Russell, ``Metareasoning for Monte Carlo Tree Search.'' Technical Report No. UCB/EECS-2011-119, EECS Department, University of California, Berkeley, 2011.
• Ronan Le Bras, Stuart Russell, Nimar Arora, and Vera Miljanovic, ``Machine Learning at the CTBTO. Testing and evaluation of the False Events Identification (FEI) and Vertically Integrated Seismic Association (VISA) project.'' In Proc. Monitoring Research Review (MRR 2011), Tucson, Arizona, 2011.
• Stuart J. Russell, Stephen C. Myers, Nimar S. Arora, David A. Moore, and Erik Sudderth, ``Bayesian Treaty Monitoring: Preliminary Report.'' In Proc. Monitoring Research Review (MRR 2011), Tucson, Arizona, 2011.
• Shaunak Chatterjee and Stuart Russell, ``A temporally abstracted Viterbi algorithm.'' In Proc. UAI-11, Barcelona, 2011.
• Nimar S. Arora, Stuart J. Russell, Paul Kidwell, and Erik Sudderth, ``Global seismic monitoring: A Bayesian approach.'' In Proc. AAAI-11, San Francisco, 2011.
• Jason Wolfe and Stuart Russell, ``Bounded Intention Planning.'' In Proc. IJCAI-11, Barcelona, 2011.
• Nimar S. Arora, Stuart J. Russell, Paul Kidwell, and Erik Sudderth, ``Global seismic monitoring as probabilistic inference.'' In Advances in Neural Information Processing Systems 23, MIT Press, 2011.
• Stuart Russell and Peter Norvig, Veštačkka inteligencija, Savremeni pristup. (Serbian translation of Artificial Intelligence: A Modern Approach, third edition.) Belgrade, CET, 2011.

• Stuart Russell and Peter Norvig, Intelligence artificielle, 3e éd.. (French translation of Artificial Intelligence: A Modern Approach, third edition.) Paris: Pearson Education France, 2010.
• Stuart Russell and Peter Norvig, Intelligenza Artificiale 3/Ed. Vol. 1 - Un Approccio Moderno. (Vol. 1 of Italian translation of Artificial Intelligence: A Modern Approach, third edition.) Rome: Pearson Italia, 2010.
• J. Claude Hemphill III, Marco D. Sorani, Stuart Russell, and Geoffrey T. Manley, ``Medical informatics.'' In P. D. Le Roux, J. M. Levine, and W. A. Kofke (Eds.), Monitoring in Neurocritical Care. Philadelphia: Elsevier, 2010.
• Ronan Le Bras, Sheila Vaidya, Jeffrey Schneider, Stuart Russell, and Nimar Arora, ``Status of the Machine Learning Efforts at the International Data Centre of the CTBTO.'' In Proc. Monitoring Research Review (MRR 2010), Orlando, Florida, 2010.
• Nimar S. Arora, Stuart J. Russell, Paul Kidwell, and Erik Sudderth, ``Global seismic monitoring as probabilistic inference.'' Technical Report No. UCB/EECS-2010-108, EECS Department, University of California, Berkeley, 2010.
• Emma Brunskill and Stuart Russell, ``RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains.'' In Proc. 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island, California, 2010.
• Nimar Arora, Stuart Russell, Rodrigo de Salvo Braz, and Erik Sudderth, ``Gibbs sampling in open-universe stochastic languages.'' In Proc. 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), Catalina Island, California, 2010.
• Stuart Russell, Sheila Vaidya, and Ronan Le Bras, ``Machine Learning for Comprehensive Nuclear-Test-Ban Treaty Monitoring.'' CTBTO Spectrum, 14, 32-35, 2010.
• Brian Milch and Stuart Russell, ``Extending Bayesian Networks to the Open-Universe Case.'' In Rina Dechter, Hector Geffner, and Joseph Y Halpern, Eds., Heuristics, Probability and Causality. A Tribute to Judea Pearl. College Publications, 2010.
• Shaunak Chatterjee and Stuart Russell, ``Why are DBNs sparse?.'' In Proc. Thirteenth International Conference on Artificial Intelligence and Statistics, Sardinia, 2010.
• Jason Wolfe, Bhaskara Marthi, and Stuart Russell, ``Combined Task and Motion Planning for Mobile Manipulation.'' In Proceedings of the Twentieth International Conference on Automated Planning and Scheduling (ICAPS 2010), Toronto, 2010.
• Stuart Russell and Peter Norvig, ``Artificial Intelligence: A Modern Approach.'' 3rd Edition, Prentice Hall, 2010.

• Stuart Russell, Nimar Arora, Michael Jordan, and Erik Sudderth, "Vertically Integrated Seismological Analysis I: Modeling." Eos Transactions of the American Geophysical Union, 90(52), Fall Meeting Supplement, Abstract S33D-08, 2009.
• Nimar Arora, Stuart Russell, and Erik Sudderth, "Vertically Integrated Seismological Analysis II: Inference." Eos Transactions of the American Geophysical Union, 90(52), Fall Meeting Supplement, Abstract S31B-1713, 2009.
• Stuart Russell and Lawrence Saul, "Technical Perspective: The Ultimate Pilot Program." Communications of the ACM, 52(7), 96-96, 2009.
• Stuart Russell, Sheila Vaidya, ``Machine Learning and Data Mining for Comprehensive Test Ban Treaty Monitoring.'' Technical Report LLNL-TR-416780, Lawrence Livermore National Laboratory, 2009.
• Rodrigo de Salvo Braz, Sriram Natarajan, Hung Bui, Jude Shavlik, and Stuart Russell, ``Anytime Lifted Belief Propagation,'' In Proc. SRL-2009, the International Workshop on Statistical Relational Learning, Leuven, Belgium, 2009.
• Songhwai Oh, Stuart Russell, and S. Shankar Sastry, ``Markov Chain Monte Carlo Data Association for Multi-Target Tracking.'' IEEE Transactions on Automatic Control, 54(3), 481-497, 2009.
• Norm Aleks, Stuart Russell, Michael G. Madden, Kristan Staudenmayer, Mitchell Cohen, Diane Morabito, and Geoffrey Manley, ``Probabilistic detection of short events, with application to critical care monitoring.'' In Advances in Neural Information Processing Systems 21, MIT Press, 2009.

• Bhaskara Marthi, Stuart Russell, and Jason Wolfe, ``Angelic Hierarchical Planning: Optimal and Online Algorithms (Revised),'' Tech. Rep. UCB/EECS-2008-150, EECS Department, University of California, Berkeley, Dec 2008.
• Stuart Russell and Peter Norvig, (Japanese translation of Artificial Intelligence: A Modern Approach, second edition.) Koichi Furukawa, translator. Tokyo: Kyoritsu Shuppan, 2008.
• Bhaskara Marthi, Stuart Russell, and Jason Wolfe, ``Angelic Hierarchical Planning: Optimal and Online Algorithms.'' In Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling (ICAPS 2008), Sydney, 2008.
• Gregory Lawrence and Stuart Russell, ``Improving Gradient Estimation by Incorporating Sensor Data.'' In Proceedings of the Twenty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI-08), Helsinki, 2008.
• Norm Aleks, Stuart Russell, Michael G. Madden, Kristan Staudenmayer, Mitchell Cohen, Diane Morabito, and Geoffrey Manley, ``Probabilistic modeling of sensor artifacts in critical care,'' In Proc. ICML-08 Workshop on Machine Learning in Health Care Applications, Helsinki, 2008.

• Jason Wolfe and Stuart Russell, ``Exploiting Belief State Structure in Graph Search.'' In Proceedings of the ICAPS 2007 Workshop on Planning in Games, Providence, Rhode Island, 2007.
• B. Marthi, S. J. Russell, and J. Wolfe, ``Angelic Semantics for High-Level Actions.'' In Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling (ICAPS 2007), Providence, Rhode Island, 2007.
• B. Marthi, S. J. Russell, and J. Wolfe, ``Angelic Semantics for High-Level Actions,'' Tech. Rep. UCB/EECS-2007-89, EECS Department, University of California, Berkeley, July 2007.
• Brian Milch, Bhaskara Marthi, Stuart Russell, David Sontag, Daniel L. Ong and Andrey Kolobov, ``BLOG: Probabilistic Models with Unknown Objects.'' In L. Getoor and B. Taskar, Eds., Introduction to Statistical Relational Learning. Cambridge, MA: MIT Press, 2007.
• Brian Milch and Stuart Russell, ``First-Order Probabilistic Languages: Into the Unknown.'' In ILP: Proceedings of the 16th International Conference on Inductive Logic Programming. Berlin: Springer, 2007.

• Stuart Russell and Peter Norvig, Intelligence artificielle, 2e éd.. (French translation of Artificial Intelligence: A Modern Approach, second edition.) Paris: Pearson Education France, 2006.
• Stuart Russell and Peter Norvig, Intelligenza Artificiale Vol. 2 Un Approccio Moderno. (Vol. 2 of Italian translation of Artificial Intelligence: A Modern Approach, second edition.) Rome: Pearson Italia, 2006.
• T. K. Satish Kumar and Stuart Russell, ``On Some Tractable Cases of Logical Filtering.'' In Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006), Ambleside, UK, 2006.
• Brian Milch and Stuart Russell, ``General-Purpose MCMC Inference over Relational Structures.'' In Proc. UAI-06, Cambridge, MA, 2006.
• Bhaskara Marthi, Stuart Russell, and David Andre, ``A Compact, Hierarchical Q-Function Decomposition.'' In Proc. UAI-06, Cambridge, MA, 2006.
• Stuart Russell and Peter Norvig, Mesterséges Intelligencia Modern Megközelitésben. (Hungarian translation of Artificial Intelligence: A Modern Approach, second edition.) Budapest, Panem Publishing, 2006.

• Stuart Russell and Peter Norvig, Искусственный интеллект: современный подход
  (Russian translation of Artificial Intelligence: A Modern Approach, second edition.) Translated by Konstantin Ptitsyn. Moscow: Williams Publishing, 2005.
• Songhwai Oh, Stuart Russell, and Shankar Sastry, ``Markov Chain Monte Carlo Data Association for Multiple-Target Tracking,'' University of California, Berkeley, Technical Report UCB//ERL M05/19, June 2005.
• Bhaskara Marthi, Stuart Russell, and David Latham, ``Writing Stratagus-Playing Agents in Concurrent ALisp.'' In Proc. IJCAI-05 Workshop on Reasoning, Representation, and Learning in Computer Games, Edinburgh, Scotland, 2005.
• Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong and Andrey Kolobov, ``BLOG: Probabilistic Models with Unknown Objects.'' In Proc. IJCAI-05, Edinburgh, Scotland, 2005.
• Stuart Russell and Jason Wolfe, ``Efficient belief-state AND-OR search, with application to Kriegspiel.'' In Proc. IJCAI-05, Edinburgh, Scotland, 2005.
• Bhaskara Marthi, Stuart Russell, David Latham, and Carlos Guestrin, ``Concurrent hierarchical reinforcement learning.'' In Proc. IJCAI-05, Edinburgh, Scotland, 2005.
• Stuart Russell and Peter Norvig, Intelligenza Artificiale Vol. 1 Un Approccio Moderno. (Vol. 1 of Italian translation of Artificial Intelligence: A Modern Approach, second edition.) Rome: Pearson Italia, 2005.
• Stuart Russell and Peter Norvig, Künstliche Intelligenz: Ein moderner Ansatz (2nd Edition). (German translation of Artificial Intelligence: A Modern Approach, second edition.) Munich: Verlag Pearson Studium, 2005.
• Brian Milch, Bhaskara Marthi, David Sontag, Stuart Russell, Daniel L. Ong and Andrey Kolobov, ``Approximate Inference for Infinite Contingent Bayesian Networks.'' In Proc. Tenth International Workshop on Artificial Intelligence and Statistics, Barbados, 2005.

• Stuart Russell and Peter Norvig, 《人工智能——一种现代方法(第二版)》 (Chinese Simplified translation of Artificial Intelligence: A Modern Approach, second edition.) Beijing: Posts and Telecommunications Press, 2004.
• Stuart Russell and Peter Norvig, Inteligencia Artificial: Un Enfoque Moderno. (Spanish translation of Artificial Intelligence: A Modern Approach, second edition.) Madrid: Pearson Educación, S. A., 2004.
• Stuart Russell and Peter Norvig, Τεχνητή Νοημοσύνη, Μια σύγχρονη προσέγγιση. (Greek translation of Artificial Intelligence: A Modern Approach, second edition.) Athens: Kleidarithmos, 2004.
• Songhwai Oh, Stuart Russell, and Shankar Sastry, ``Markov Chain Monte Carlo Data Association for General Multiple Target Tracking Problems.'' In Proc. 43rd IEEE Conference on Decision and Control (CDC-04), Paradise Island, Bahamas, 2004.
• Stuart Russell and Peter Norvig, Inteligencia Artificial. (Portuguese translation of Artificial Intelligence: A Modern Approach, second edition.) Rio de Janeiro: Elsevier/Editora Campus, 2004.
• Eric Xing, Michael Jordan, and Stuart Russell, ``Graph partition strategies for generalized mean field inference.'' In Proc. UAI-04, Banff, Alberta, 2004.
• Brian Milch, Bhaskara Marthi, and Stuart Russell, ``BLOG: Relational Modeling with Unknown Objects.'' In Proc. ICML-04 Workshop on Statistical Relational Learning, Banff, Canada, 2004.
• Bhaskara Marthi, David Latham, Carlos Guestrin, Stuart Russell, ``Concurrent Hierarchical Reinforcement Learning.'' In Proc. AAAI-04 Workshop on Learning and Planning in Markov Processes, San Jose, 2004.

• Stuart Russell and Peter Norvig, ``Solution Manual for Artificial Intelligence: A Modern Approach.'' 2nd Edition, Prentice Hall, 2003.
• Eyal Amir and Stuart Russell, ``Logical Filtering.'' In Proc. IJCAI-03, Acapulco, Mexico, 2003.
• Bhaskara Marthi, Brian Milch, and Stuart Russell, ``First-Order Probabilistic Models for Information Extraction.'' In Proc. IJCAI-03 Workshop on Learning Statistical Models from Relational Data, Acapulco, Mexico, 2003.
• Stuart Russell and Andrew Zimdars, ``Q-Decomposition for Reinforcement Learning Agents.'' In Proc. ICML-03, Washington, DC, 2003.
• Greg Lawrence, Noah Cowan, and Stuart Russell, ``Efficient Gradient Estimation for Motor Control Learning.'' In Proc. UAI-03, Acapulco, Mexico, 2003.
• Eric P. Xing, Michael I. Jordan, and Stuart Russell, ``A generalized mean field algorithm for variational inference in exponential families.'' In Proc. UAI-03, Acapulco, Mexico, 2003.
• Eyal Amir and Stuart Russell, ``Temporal Logical Filtering---Preliminary Results.'' In Proc. Common Sense 2003, Stanford, CA, 2003.
• Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart Russell, ``Distance Metric Learning, with application to Clustering with side-information.'' In Advances in Neural Information Processing Systems 15, MIT Press, 2003.
• Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart Russell, and Ilya Shpitser, ``Identity Uncertainty and Citation Matching.'' In Advances in Neural Information Processing Systems 15, MIT Press, 2003.
• Eric P. Xing, Michael I. Jordan, Richard M. Karp, and Stuart Russell, ``A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences.'' In Advances in Neural Information Processing Systems 15, MIT Press, 2003.
• Judea Pearl and Stuart Russell, ``Bayesian Networks.'' In Michael A. Arbib, Ed., The Handbook of Brain Theory and Neural Networks, 2nd edition, MIT Press, 2003.
• Stuart Russell and Peter Norvig, ``Artificial Intelligence: A Modern Approach.'' 2nd Edition, Prentice Hall, 2003.

• Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres, ``Decayed MCMC Filtering.'' In Proc. UAI-02, Edmonton, Alberta: Morgan Kaufmann, 2002.
• David Andre and Stuart Russell, ``State Abstraction for Programmable Reinforcement Learning Agents.'' In Proc. AAAI-02, Edmonton, Alberta: AAAI Press, 2002.
• Michael Shilman, Hanna Pasula, Stuart Russell, and Richard Newton, ``Statistical Visual Language Models for Ink Parsing.'' In Proc. AAAI Spring Symposium on Sketch Understanding, Stanford, March 2002.
• Stuart Russell, `` Rationality and Intelligence.'' In Renee Elio (Ed.), Common sense, reasoning, and rationality, Oxford University Press, 2002.

• David Andre and Stuart Russell, ``State Abstraction for Programmable Reinforcement Learning Agents.'' Technical Report CSD-01-1156, Computer Science Division, UC Berkeley, 2001.
• Nikunj Oza and Stuart Russell, ``Experimental Comparisons of Online and Batch Versions of Bagging and Boosting.'' In Proc. KDD-01, San Francisco, 2001.
• Kevin Murphy and Stuart Russell, ``Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.'' In Sequential Monte Carlo Methods in Practice, A. Doucet, N. de Freitas and N.J. Gordon (eds), Springer-Verlag, 2001.
• Joao de Freitas, Pedro Hoejen-Soerensen, Michael Jordan, and Stuart Russell, ``Variational MCMC.'' In Proc. UAI-01, Seattle, 2001.
• Hanna Pasula and Stuart Russell, ``Approximate inference for first-order probabilistic languages.'' In Proc. IJCAI-01, Seattle, 2001.
• Stuart Russell, ``Identity uncertainty.'' In Proc. IFSA-01, Vancouver, 2001.
• Nikunj Oza and Stuart Russell, ``Online Bagging and Boosting.'' In Eighth International Workshop on Artificial Intelligence and Statistics, Key West, Florida. 2001
• David Andre and Stuart Russell, ``Programmable Reinforcement Learning Agents.'' In Advances in Neural Information Processing Systems 13, MIT Press, 2001.

• Andrew Y. Ng and Stuart Russell, ``Algorithms for inverse reinforcement learning.'' In Proceedings of the Seventeenth International Conference on Machine Learning, Stanford, California: Morgan Kaufmann, 2000.
• Arnaud Doucet, Nando de Freitas, Kevin Murphy, and Stuart Russell, ``Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.'' In Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence , Stanford, California: Morgan Kaufmann, 2000.

• Stuart Russell and Peter Norvig, Mesterséges Intelligencia Modern Megközelitésben. (Hungarian translation of Artificial Intelligence: A Modern Approach.) Budapest, Panem Publishing, 1999.
• Stuart Russell, ``Expressive probability models for speech recognition and understanding.'' In Proc. International Workshop on Automatic Speech Recognition and Understanding (ASRU), Keystone, Colorado, 1999 (invited paper).
• Stuart Russell, ``Expressive probability models in science.'' In Proc. 2nd Int'l Conf. on Discovery Science, Tokyo, Japan: Springer Verlag, 1999 (invited paper).
• Geoffrey Zweig and Stuart Russell, ``Probabilistic modeling with Bayesian networks for automatic speech recognition.'' Australian Journal of Intelligent Information Processing Systems, 5(4), 253-60, 1999 (invited paper).
• Andrew Y. Ng, Daishi Harada, and Stuart Russell, ``Policy invariance under reward transformations: Theory and application to reward shaping.'' In Proc. ICML-99, Bled, Slovenia, 1999.
• Vassilis Papavassiliou and Stuart Russell, ``Convergence of reinforcement learning with general function approximators.'' In Proc. IJCAI-99, Stockholm, 1999.
• Hanna Pasula, Stuart Russell, Michael Ostland, and Ya'acov Ritov, ``Tracking many objects with many sensors.'' In Proc. IJCAI-99, Stockholm, 1999.
• Daishi Harada and Stuart Russell, ``Extended abstract: Learning search strategies.'' In Proc. AAAI Spring Symposium on Search Techniques for Problem Solving under Uncertainty and Incomplete Information, Stanford, CA, 1999.

• Stuart Russell and Peter Norvig, (Japanese translation of Artificial Intelligence: A Modern Approach.) Koichi Furukawa, translator. Tokyo: Kyoritsu Shuppan, 1998.
• G. Zweig and S. Russell, ``Probabilistic Modeling with Bayesian Networks for ASR.'' In Proc. ICSLP-98, Sydney, Australia, 1998.
• Michael Jordan and Stuart Russell, ``Computational Intelligence.'' In The MIT Encyclopedia of the Cognitive Sciences, MIT Press, 1998. [The version linked here is in draft form.]
• Stuart Russell, ``Metareasoning.'' In The MIT Encyclopedia of the Cognitive Sciences, MIT Press, 1998.
• Prasad Tadepalli and Stuart Russell, ``Learning from Examples and Membership Queries with Structured Determinations.'' Machine Learning, 32, 245-95, 1998.
• Tim Huang and Stuart Russell, ``Object Identification: A Bayesian Analysis with Application to Traffic Surveillance.'' Artificial Intelligence, 103, 1-17, 1998 (invited paper).
• G. Zweig and S. Russell, ``Speech Recognition with Dynamic Bayesian Networks.'' In Proc. AAAI-98, Madison, Wisconsin: AAAI Press, 1998.
• R. Dearden, N. Friedman, and S. Russell, ``Bayesian Q-Learning.'' In Proc. AAAI-98, Madison, Wisconsin: AAAI Press, 1998.
• N. Friedman, K. Murphy, and S. Russell, ``Learning the Structure of Dynamic Probabilistic Networks.'' In Proc. UAI-98, Madison, Wisconsin: Morgan Kaufmann, 1998.
• S. Russell, ``Learning agents for uncertain environments (extended abstract).'' In Proc. COLT-98, Madison, Wisconsin: ACM Press, 1998.
• N. Friedman, K. Murphy, and S. Russell, ``Learning the Structure of Dynamic Probabilistic Networks.'' In Proc. Conference on Automated Learning and Discovery, Pittsburgh, June 1998.
• Ron Parr and Stuart Russell, ``Reinforcement Learning with Hierarchies of Machines.'' In Advances in Neural Information Processing Systems 10, MIT Press, 1998.
• Vassilis Papavassiliou and Stuart Russell, ``Value Determination with General Function Approximators.'' Technical Report CSD-98-1005, Computer Science Division, UC Berkeley, 1998.

• Geoffrey Zweig and Stuart Russell, Compositional Modeling with DPNs. Technical Report No.~CSD-97-970, Computer Science Division, University of California, Berkeley, 1997.
• Jeffrey Forbes, Nikunj Oza, Ronald Parr, and Stuart Russell, Feasibility Study of Fully Automated Vehicles Using Decision-Theoretic Control. California PATH Research Report UCB-ITS-PRR-97-18, Institute of Transportation Studies, University of California, Berkeley. April 1997.
• Jitendra Malik and Stuart Russell, Traffic Surveillance and Detection Technology Development: New Traffic Sensor Technology Final Report. California PATH Research Report UCB-ITS-PRR-97-6, Institute of Transportation Studies, University of California, Berkeley. January 1997.
• John Binder, Daphne Koller, Stuart Russell, Keiji Kanazawa, `` Adaptive Probabilistic Networks with Hidden Variables.'' Machine Learning, 29, 213--244, 1997.
• Stuart Russell, `` Rationality and Intelligence.'' Artificial Intelligence, 94, 57--77, 1997.
• Nir Friedman, Moises Goldszmidt, David Heckerman, Stuart Russell, `` Where is the Impact of Bayesian Networks in Learning? .'' In Proc. Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
• John Binder, Kevin Murphy, Stuart Russell, ``Space-Efficient Inference in Dynamic Probabilistic Networks.'' In Proc. Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
• Timothy Huang, Stuart Russell, `` Object Identification in a Bayesian Context.'' Distinguished paper award, in Proc. Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997.
• Nir Friedman, Stuart Russell, ``Image Segmentation in Video Sequences.'' In Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Providence, Rhode Island: Morgan Kaufmann, 1997.

• Stuart Russell, ``Machine Learning.'' Chapter 4 of M. A. Boden (Ed.), Artificial Intelligence, Academic Press, 1996. Part of the Handbook of Perception and Cognition. [The version linked here is in draft form.]
• Shlomo Zilberstein and Stuart Russell ``Optimal composition of real-time systems.'' Artificial Intelligence, 82(1-2), pp.181-213, 1996.

• Stuart Russell and Peter Norvig, Solution Manual for "Artificial Intelligence: A Modern Approach." Englewood Cliffs, NJ: Prentice Hall; 1995.
• Stuart Russell, ``Rationality and Intelligence.'' Invited paper (Computers and Thought Award), in Proc. Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
• Jeff Forbes, Tim Huang, Keiji Kanazawa, and Stuart Russell, ``The BATmobile: Towards a Bayesian Automated Taxi.'' In Proc. Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
• Ron Parr and Stuart Russell, ``Approximating Optimal Policies for Partially Observable Stochastic Domains.'' In Proc. Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
• Stuart Russell, John Binder, Daphne Koller, and Keiji Kanazawa, ``Local learning in probabilistic networks with hidden variables.'' In Proc. Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada, 1995.
• Keiji Kanazawa, Daphne Koller, and Stuart Russell, ``Stochastic simulation algorithms for dynamic probabilistic networks.'' In Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, Montreal, Canada: Morgan Kaufmann, 1995.
• Jeff Forbes, Tim Huang, Keiji Kanazawa, and Stuart Russell, ``The BATmobile: Towards a Bayesian Automated Taxi.'' In SAE Future Transportation Technology Conference, Costa Mesa, CA, August, 1995.
• Stuart Russell and Devika Subramanian ``Provably bounded-optimal agents.'' Journal of Artificial Intelligence Research, 2, 1995.
• Armand Prieditis and Stuart Russell (Eds.), Machine Learning: Proceedings of the Twelfth International Conference, Tahoe City, CA: Morgan Kaufmann, 1995.
• Shlomo Zilberstein and Stuart Russell, ``Approximate reasoning using anytime algorithms.'' In S. Natarajan (Ed.) Imprecise and Approximate Computation, Kluwer Academic Publishers, Dordrecht, 1995.
• Saso Dzeroski, Stephen Muggleton and Stuart Russell ``PAC-Learnability of Constrained, Nonrecursive Logic Programs.'' In T. Petsche, S. Hanson, and J. Shavlik (Eds.), Computational Learning Theory and Natural Learning Systems, Volume III: Selecting Good Models, MIT Press, 1995.

• Stuart Russell and Peter Norvig Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice Hall, 1994.
• Stuart Russell and Peter Norvig, ``A Modern, Agent-Oriented Approach to AI Instruction.'' In Proceedings of the AAAI Fall Symposium on Innovative Instruction for Introductory AI, New Orleans, Nov. 1994.
• Scott Davies and Stuart Russell, ``NP-completeness of searches for smallest possible feature sets.'' In Proceedings of the AAAI Fall Symposium on Relevance, New Orleans, Nov. 1994.
• D. Koller, J Weber, T. Huang, J. Malik, G. Ogasawara, B. Rao, and S. Russell, ``Towards Robust Automatic Traffic Scene Analysis in Real-Time.'' In Proceedings of the International Conference on Pattern Recognition, Israel, Nov. 1994.
• J. Tash and S. Russell ``Control strategies for a stochastic planner.'' In Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA, 1994.
• T. Huang, D. Koller, J. Malik, G. Ogasawara, B. Rao, S. Russell, and J. Weber. ``Automatic symbolic traffic scene analysis using belief networks.'' In Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA, 1994.
• Stuart Russell, John Binder, and Daphne Koller, ``Adaptive probabilistic networks.'' Technical report UCB//CSD-94-824, July 24, 1994.

• Stuart Russell and Devika Subramanian ``On Provably RALPHs.'' In E. Baum (Ed.) Computational Learning and Cognition: Proceedings of the Third NEC Research Symposium. SIAM Press, 1993.
• Tim Huang, Gary Ogasawara, and Stuart Russell ``Symbolic Traffic Scene Analysis Using Belief Networks.'' In Proc. AAAI Workshop on AI in Intelligent Vehicle and Highway Systems, Washington, DC, 1993.
• Brenda Barbour and Stuart Russell ``Experiments in Adaptive Indexing for Logic Programming.'' In Proceedings of the ICML-93 Workshop on Knowledge Compilation and Speedup Learning, Amherst, MA, June 1993.
• Stuart Russell and Devika Subramanian ``Constructing bounded optimal systems.'' In Proc. AAAI Spring Symposium on AI and NP-hard problems, Stanford, CA, March 1993.
• Gary Ogasawara and Stuart Russell ``Decision-theoretic planning with multiple execution architectures.'' Proc. AAAI Spring Symposium on AI Planning, Stanford, CA, March 1993.
• S. Zilberstein and S. J. Russell. ``Anytime Sensing, Planning and Action: A Practical Model for Robot Control.'' In Proc. Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France, 1993.
• Stuart Russell, Devika Subramanian, and Ronald Parr, ``Provably bounded optimal agents.'' In Proc. Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France, 1993.
• Gary Ogasawara and Stuart Russell ``Planning Using Multiple Execution Architectures.'' In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, Chambery, France: Morgan Kaufmann, 1993.
• Musick, R., Catlett, J. and Russell, S. ``An Efficient Method for Constructing Approximate Decision Trees for Large Databases.'' In Proceedings of the Tenth International Conference in Machine Learning, Amherst, MA, 1993.
• Ann Nicholson and Stuart Russell, ``Techniques for Handling Inference Complexity in Dynamic Belief Networks.'' Technical report no. CS-93-31, Computer Science Department, Brown University, 1993.

• Shlomo Zilberstein and Stuart Russell ``Constructing utility-driven real-time systems using anytime algorithms.'' Proc. IEEE Workshop on Imprecise and Approximate Computation, Phoenix, AZ, December, 1992.
• Shlomo Zilberstein and Stuart Russell ``Control of Mobile Robots Using Anytime Computation.'' In Proceedings of the AAAI Fall Symposium on Applications of Artificial Intelligence to Real-World Autonomous Mobile Robots, Cambridge, MA, October, 1992.
• Shlomo Zilberstein and Stuart Russell ``Reasoning about optimal allocation of time using conditional performance profiles.'' In Proc. AAAI-92 Workshop on Implementations of Temporal Reasoning, San Jose, CA, July, 1992.
• Saso Dzeroski, Stephen Muggleton and Stuart Russell ``PAC-Learnability of Constrained, Nonrecursive Logic Programs.'' In Proceedings of the Third International Workshop on Computational Learning Theory and Natural Learning Systems (CLNL-92), Madison, WI, 1992.
• Stuart Russell ``Efficient Memory-Bounded Search Methods.'' In Proceedings of the Tenth European Conference on Artificial Intelligence, Vienna: Wiley, 1992.
• Saso Dzeroski, Stephen Muggleton and Stuart Russell ``PAC-Learnability of Determinate Logic Programs.'' In Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory (COLT-92), Pittsburgh, PA: ACM Press, 1992.
• Ronald Musick and Stuart Russell ``How Long Will It Take?'' In Proceedings of the Tenth National Conference on Artificial Intelligence, San Jose, CA: AAAI Press, 1992.
• Shlomo Zilberstein and Stuart Russell ``Efficient Resource-Bounded Reasoning in AT-RALPH.'' In Proceedings of the First International Conference on AI Planning Systems, College Park, Maryland: Morgan Kaufmann, 1992.

• Stuart Russell ``An Architecture for Bounded Rationality.'' In Proceedings of the AAAI Symposium on Integrated Architectures for Intelligent Agents, Stanford, March, 1991. Also in Proceedings of the IJCAI Workshop on Theoretical and Practical Design of Rational Agents, Sydney, August, 1991.
• Stuart Russell and Shlomo Zilberstein ``Composing Real-Time Systems.'' In Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, Sydney, Australia: Morgan Kaufmann, 1991.
• Stuart Russell ``Inductive Learning by Machines.'' Philosophical Studies 64(1), 1991.
• Stuart Russell ``Prior Knowledge and Autonomous Learning.'' Journal of Robotics and Autonomous Systems 8, 1991.
• Stuart Russell ``An Architecture for Bounded Rationality.'' SIGART Bulletin 2(4), 1991.
• Stuart Russell and Eric Wefald ``Principles of Metareasoning.'' Artificial Intelligence 49, 1991.
• Stuart Russell and Eric H. Wefald Do the Right Thing: Studies in Limited Rationality. Cambridge, MA: MIT Press, 1991.

• Todd R. Davies and Stuart Russell ``A Logical Approach to Reasoning by Analogy.'' In T. Dietterich (Ed.) Readings in Machine Learning. San Mateo, CA: Morgan Kaufmann, 1990.
• Sampath Srinivas, Stuart Russell, and Alice Agogino, ``Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information.'' In M. Henrion, R. D. Shachter, L. N. Kanal, and J. F. Lemmer (Eds.) Uncertainty in Artificial Intelligence 5. Amsterdam: North Holland, 1990.
• Stuart Russell ``Prior Knowledge and Autonomous Learning.'' In Maes, P. and van der Velde, W. (Eds.) Representation and Learning in an Autonomous Agent. Cambridge, MA: MIT Press, 1990.
• Benjamin Grosof and Stuart Russell ``Shift of Bias as Nonmonotonic Reasoning.'' In Brazdil, P., and Konolige, K. (Eds.) Machine Learning, Meta-Reasoning and Logics. Dordrecht: Kluwer Academic Publishers, 1990.
• Stuart Russell and Benjamin Grosof ``A Sketch of Autonomous Learning using Declarative Bias.'' In Brazdil, P., and Konolige, K. (Eds.) Machine Learning, Meta-Reasoning and Logics. Dordrecht: Kluwer Academic Publishers, 1990.
• Stuart Russell and Devika Subramanian ``Mutual Constraints on Representation and Inference.'' In Brazdil, P., and Konolige, K. (Eds.) Machine Learning, Meta-Reasoning and Logics. Dordrecht: Kluwer Academic Publishers, 1990.
• Othar Hansson, Andrew Mayer, and Stuart Russell, ``Decision-theoretic planning in BPS.'' In Proceedings of the AAAI Symposium on Planning in Uncertain Environments, Stanford, March, 1990.
• Stuart Russell ``Fine-grained decision-theoretic search control.'' In Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA: Morgan Kaufmann, 1990.

• Benjamin Grosof and Stuart Russell ``Declarative Bias for Structural Domains.'' Research report no. RC 14620 (#64608), IBM Research Division, 1989.
• Benjamin Grosof and Stuart Russell ``Shift of Bias as Nonmonotonic Reasoning.'' Research report no. RC 14614 (#65293), IBM Research Division, 1989.
• Stuart Russell and Benjamin Grosof ``A Sketch of Autonomous Learning using Declarative Bias.'' Research report no. RC 14613 (#64812), IBM Research Division, 1989.
• Stuart Russell and Benjamin Grosof ``Declarative Bias: An Overview.'' In Benjamin, P. (Ed.) Change of Representation and Inductive Bias, Dordrecht: Kluwer Academic Publishers, 1989.
• Eric Wefald and Stuart Russell, ``Estimating the value of computation: The case of real-time search.'' In Proceedings of the AAAI Symposium on AI and Limited Rationality, Stanford, March, 1989.
• Sampath Srinivas, Stuart Russell, and Alice Agogino, ``Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information.'' In Proceedings of the Fifth Workshop on Uncertainty in Artificial Intelligence, Windsor, Ontario, 1989.
• Benjamin Grosof and Stuart Russell ``Declarative Bias for Structural Domains.'' In Proceedings of the Sixth International Workshop on Machine Learning, Ithaca, NY: Morgan Kaufmann, 1989.
• Eric Wefald and Stuart Russell ``Adaptive Learning of Decision-Theoretic Search Control Knowledge.'' In Proceedings of the Sixth International Workshop on Machine Learning, Ithaca, NY: Morgan Kaufmann, 1989.
• Stuart Russell and Eric Wefald ``On optimal game-tree search using rational metareasoning.'' In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI: Morgan Kaufmann, 1989.
• Stuart J. Russell ``Execution architectures and compilation.'' In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI: Morgan Kaufmann, 1989.
• Stuart Russell and Eric Wefald ``Principles of Meta-Reasoning.'' In Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, Toronto, Ontario: Morgan Kaufmann, 1989.
• Michael Braverman and Stuart Russell ``Boundaries of Operationality.'' In Proceedings of the Fifth International Conference on Machine Learning, Ann Arbor, MI: Morgan Kaufmann, 1989.
• Stuart Russell The Use of Knowledge in Analogy and Induction. London: Pitman, 1989.

• Alice Agogino, Ramanathan Guha and Stuart Russell ``Sensor Fusion using Influence Diagrams and Reasoning by Analogy: Application to Milling Machine Monitoring and Control.'' Working paper 88-0304-P, Department of Mechanical Engineering, University of California, Berkeley, CA, 1988.
• Stuart Russell and Eric Wefald, ``Decision-Theoretic Search Control: General Theory and an Application to Game-Playing.'' Computer Science Division Technical Report 88/435, University of California, Berkeley, CA, 1988.
• Stuart Russell ``Analogy by Similarity.'' In David Helman (Ed.), Analogical Reasoning, Boston, MA: D. Reidel, 1988.
• Benjamin Grosof and Stuart Russell ``Shift of Bias as Nonmonotonic Reasoning.'' In Proceedings of the International Workshop on Machine Learning, Meta-Reasoning and Logics, Sesimbra, Portugal, 1988.
• Stuart Russell and Benjamin Grosof ``A Sketch of Autonomous Learning using Declarative Bias.'' In Proceedings of the International Workshop on Machine Learning, Meta-Reasoning and Logics, Sesimbra, Portugal, 1988.
• Stuart Russell and Devika Subramanian ``Mutual Constraints on Representation and Inference.'' In Proceedings of the International Workshop on Machine Learning, Meta-Reasoning and Logics, Sesimbra, Portugal, 1988.
• Michael Braverman and Stuart Russell ``Explanation-Based Learning in Complex Domains.'' In AAAI Symposium on Explanation-Based Learning, Stanford, March, 1988.
• Stuart Russell and Eric Wefald ``Multi-Level Decision-Theoretic Search.'' In AAAI Symposium on Computer Game-Playing, Stanford, March, 1988.
• Alice Agogino, Ramanathan Guha and Stuart Russell ``Sensor Fusion using Influence Diagrams and Reasoning by Analogy: Application to Milling Machine Monitoring and Control.'' In Proceedings of the Third International Conference on Applications of Artificial Intelligence in Engineering, Stanford, CA: Computational Mechanics Institute, 1988.
• Stuart Russell ``Tree-Structured Bias.'' In Proceedings of the Seventh National Conference on Artificial Intelligence, Minneapolis, MN: Morgan Kaufmann, 1988.
• Michael Braverman and Stuart Russell ``IMEX: Overcoming Intractability in Explanation-Based Learning.'' In Proceedings of the Seventh National Conference on Artificial Intelligence, Minneapolis, MN: Morgan Kaufmann, 1988.

• Stuart Russell ``Rationality as an Explanation of Language?.'' Behavioral and Brain Sciences 10, 1987.
• Stuart Russell ``Analogy and Single-Instance Generalization.'' In Proceedings of the Fourth International Machine Learning Workshop, Irvine, CA: Morgan Kaufmann, 1987.
• Todd R. Davies and Stuart Russell ``A Logical Approach to Reasoning by Analogy.'' In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, Milan, Italy: Morgan Kaufmann, 1987.
• Stuart Russell and Benjamin Grosof ``A Declarative Approach to Bias in Concept Learning.'' In Proceedings of the Sixth National Conference on Artificial Intelligence, Seattle, WA: Morgan Kaufmann, 1987.

• Stuart Russell ``Analogical and Inductive Reasoning.'' Ph. D. Thesis, Stanford University Department of Computer Science, December 1986. Also appeared as Stanford University Computer Science Department Technical Report STAN-CS-87-1150.
• Stuart Russell ``A Quantitative Analysis of Analogy by Similarity.'' In Proceedings of the Fifth National Conference on Artificial Intelligence, Philadelphia, PA: Morgan Kaufmann, 1986.
• Stuart Russell ``Preliminary Steps Toward the Automation of Induction.'' In Proceedings of the Fifth National Conference on Artificial Intelligence, Philadelphia, PA: Morgan Kaufmann, 1986.
• Todd R. Davies and Stuart Russell, ``A Logical Approach to Reasoning by Analogy.'' SRI AI Center Technical Note 385; 1986.

• Stuart Russell ``The Compleat Guide to MRS.'' Stanford University Computer Science Department Report No. STAN-CS-85-1080; June 1985 126pp. Also published as Stanford Knowledge Systems Laboratory Report No. KSL-85-12.