Oregon State University 4 credits AI
Introduce key concepts in intelligent decision-making, specifically reinforcement learning. Topics include agent representation, Markov decision process, fundamentals of model-free and model-based decision-making under uncertainty, value iteration, policy iteration, temporal difference methods, actor-critic methods, and imitation learning.
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