Web Reference: In value function approximation, target is r + V^ˇ(s0;w), a biased and approximated estimate of the true value Vˇ(s) Can reduce doing TD(0) learning with value function approximation to supervised learning on a set of data pairs: Nonlinear Value Function Approximation • Use artificial neural networks state S parameter Apr 14, 2023 · Function approximation methods offer a solution for tasks with arbitrarily large state spaces, where conventional state or state-action tables are impractical due to memory constraints or an inability to optimally fill them even with infinite time and data.
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