Original Proposal: Stochastic Optimizer with Learning

• Goals:

  • Use incremental learning (Bayesian, SVM) to capture knowledge
  • Use stochastic pattern recognition
  • Train using well-characterized problems
    • Physical design, Logic synthesis
  • Identify effective approaches to parallel implementation

Working Memory

Stochastic

Inference

Engine

Move Set

Complex

Objective Function

Domain-Specific

“Knowledge Pack”

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