Linear function approximation - PowerPoint PPT Presentation

Function approximation

Function approximation. Nisheeth 31 st January 2019. The state space problem in model-free RL. Number of states quickly becomes too large Even for trivial applications Learning becomes too dependent on right choice of exploration parameters

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Algorithms For Inverse Reinforcement Learning

Algorithms For Inverse Reinforcement Learning. Presented by Alp Sardağ. Goal. Given the observed optimal behaviour extract a reward function. It may be useful: In apprenticeship learning For ascertaining the reward function being optimized by a natural system. The problem. Given :

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