Planning and acting in partially observable stochastic domains
1998/05/01 by Leslie Pack Kaelbling, Michael L. Littman, Anthony R. Cassandra · 290 citations
Computer Science · #Formal Methods in Verification #AI-based Problem Solving and Planning #Logic, Reasoning, and Knowledge
paper · doi:10.1016/s0004-3702(98)00023-x
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- Reward Maximization Through Discrete Active Inference. [europepmc]
- Emergence of belief-like representations through reinforcement learning. [europepmc]