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Temporal Difference learning is one of the most used approaches for policy evaluation. It is a central part of solving reinforcement learning tasks. For deriving optimal control, policies have to be evaluated. This task requires value function approximation. At this point TD methods find application. The use of eligibility traces for backpropagation of(More)
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