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Reinforcement Learning
Published on Feb 25, 20077221 Views
Reinforcement learning is about learning good control policies given only weak performance feedback: occasional scalar rewards that might be delayed from the events that led to good performance. Reinf
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Chapter list
Reinforcement Learning00:06
Outline01:00
Reinforcement Learning (RL) in a Nutshell01:46
RL Can Solve Hard Problems04:10
Examples07:58
Partially Observable Markov Decision Processes08:47
Types of RL14:17
Optimality Criteria16:03
Criteria Continued17:45
Discounted or Average?19:10
Average versus Discounted21:15
Dynamic Programming23:05
Analytic Solution27:12
Value Iteration28:34
Value Iteration Continued29:49
Value Iteration Convergence32:32
Policy Iteration34:17
Policy Iteration, Pros and Cons36:35
Convergence Picture37:38
Our Progress...38:54