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Allen's REINFORCE notes

No change in size, 24 May
Motivation
=== Motivation ===
Recall that the objective of Reinforcement Learning is to find an optimal policy <math>\pi^*<\math> which we encode in a neural network with parameters <math>\theta^*<\/math>. These optimal parameters are defined as<math>\theta^* = \text<argmax>_\theta E_{\tau \sim p_\theta(\tau)} \left[ \sum_t r(s_t, a_t) \right] <\/math>
=== Learning ===
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