We are interested in the design of single and multi-agent systems that deliver high levels of mission reliability in dynamic and rapidly evolving environments. Multi-agent systems that coordinate intelligently to optimize a system-wide objective offer interesting possibilities for achieving massive mission reliability through enhanced survivability and reusability, if they are co-ordinated in a distributed control paradigm together with decentralization of information. The decentralization of control intelligence and information suggests the possibility of high tolerance to effector or sensor degradation in individual agents through rapid and variable dynamic reconfiguration of inter-agent co-ordination protocols and individual agent operating modes. We have had a great deal of experience at Berkeley on two large civilian (or dual use) test beds: the first for Automated Highway Systems (AHS) and the other for Air Traffic Management Systems (ATMS) in multi-agent systems. It is this experience that convinces us that the design of reliable multi-agent systems is a difficult problem. It needs research into a new system-theoretic paradigm that we broadly characterize as hierarchical semi-autonomous agent control. In distributed, decentralized control applications for multi-agent systems, it is important to be able to evaluate hierarchies and heterarchies of control architectures for the following reasons:
If the performance degradation of a completely decentralized solution is unacceptable and a completely centralized solution is prohibitively complex or expensive, a compromise will have to be found. Such a compromise will feature semi-autonomous agent operation. In this case, each agent is trying to optimize its own usage of the resource and coordinates with ``neighboring'' agents and a base station in case there is a conflict of objectives. It should be noted that semiautonomous agent control is naturally suited for hybrid designs. At the continuous level, each agent chooses its own optimal strategy, while discrete coordination is used to resolve conflicts. Thus, the class of hybrid systems that we will be most interested in are semi-autonomous multi-agent systems, where the hybrid dynamics arise from the interaction between continuous single agent ``optimal'' strategies and discrete conflict resolution or coordination protocols.
There is a continuum of design choices for system decomposition, ranging from strict hierarchical control to a fully distributed, multi-agent system. Furthermore, different choices may be appropriate at different levels of abstraction, ranging from the (typically continuous-domain) low-level control systems concerned with safety and smooth execution to the (typically symbolic/discrete) strategic levels concerned with optimization and planning for high-level goals. We will investigate theoretical and design issues involved in the choice of system architecture, and methods for interfacing elements of the resulting hybrid system.