Working with Linear Function Approximation part2(Machine Learning)
Exponential Hardness of Reinforcement Learning with Linear Function Approximation(arXiv) Author : Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan, Csaba Szepesvári, Gellért Weisz Abstract : A fundamental question in reinforcement learning theory is: suppose the optimal value functions are linear in given features, can we learn them efficiently? This problem’s…
Working with Linear Function Approximation part2(Machine Learning) Exponential Hardness of Reinforcement Learning with Linear Function Approximation(arXiv) Author : Daniel Kane, Sihan Liu, Shachar Lovett, Gaurav Mahajan, Csaba Szepesvári, Gellért Weisz Abstract : A fundamental question in reinforcement learning theory is: suppose the optimal value functions are linear in given features, can we learn them efficiently? This problem’s… machine-learning
Working Linear Function Approximation part2Machine Learning Exponential Hardness Reinforcement Learning Linear Function ApproximationarXiv Author Daniel Kane Sihan Liu Shachar Lovett Gaurav Mahajan Csaba Szepesvári Gellért Weisz Abstract fundamental question reinforcement learning theory suppose optimal value function linear given feature learn efficiently problem’s… machinelearning