Book details
Decision Making Under Uncertainty
Categories Artificial intelligence
Decision Making Under Uncertainty develops probabilistic models and decision-theoretic methods for building agents that act when outcomes are uncertain. It covers Bayesian networks and inference, utility and games, Markov decision processes, planning, reinforcement learning, and model uncertainty.
