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It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL).
A new heuristic adaptive state aggregation algorithm that finds improved compact representations by exploiting the non-discrete nature of soft state ...
It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms to ...
This paper presents a function approximator based on a simple extension to state aggregation (a commonly used form of compact representation), namely soft ...
PDF | It is widely accepted that the use of more compact representations than lookup tables is crucial to scaling reinforcement learning (RL) algorithms.
Feb 6, 2019 · Protected: Reinforcement Learning with Soft State Aggregation. This content is password protected. To view it please enter your password ...
Mar 29, 2022 · State aggregation is a simple form of generalizing function approximation in which states are grouped together, with one estimated value (one component of the ...
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Reinforcement Learning with Soft State Aggregation. Reinforcement Learning with Soft State Aggregation Satinder P. Singh, Tommi Jaakkola, and Michael I.
This article presents the use of fuzzy state aggregation with the current policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF ...
Abstract. In this paper we discuss policy iteration methods for approximate solution of a finite-state discounted. Markov decision problem, with a focus on ...