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CS 188: Artificial Intelligence Example: Grid World
If there is a wall in the direction the agent would have been taken, the agent stays put The agent receives rewards each time step Small “living” reward each step (can be negative) Big rewards come at the end (good or bad) Goal: maximize sum of (discounted) rewards Recap: MDPs Markov decision processes: States S
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