| The Learning Task |
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| • | Markov
Decision Process (MDP) |
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| – | finite
set of states S |
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| – | finite
set of actions A |
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| – | st+1 = d(st, at), reward rt
= r(st, at) |
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| • | d and r are part of the environment and not
necessarily known |
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| • | d and r may be nondeterministic (we begin with
assumption of |
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| determinism) |
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| • | Learn
policy p : S à A optimizing some function |
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| of
reward over time for MDP |
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