Approximate Policy Iteration for several Environments and Reinforcement Functions
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چکیده
We state an approximate policy iteration algorithm to find stochastic policies that optimize single-agent behavior for several environments and reinforcement functions simultaneously. After introducing a geometric interpretation of policy improvement for stochastic policies we discuss approximate policy iteration and evaluation. We present examples for two blockworld environments and reinforcement functions.
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تاریخ انتشار 2003