A Reinforcement Learning Algorithm Based on Policy Iteration for Average Reward Empirical Results with Yield Management and Convergence Analysis.

A Reinforcement Learning Algorithm Based on Policy Iteration for Average Reward Empirical Results with Yield Management and Convergence Analysis.

We present a Reinforcement Learning (RL) algorithm based on policy iteration for solving average reward Markov and semi-Markov decision problems. In the literature on discounted reward RL, algorithms based on policy iteration and actor-critic algorithms have appeared. Our algorithm is an asynchronou...

詳細記述

書誌詳細
出版年:Machine learning. 55, 1 (2004).
第一著者: Gosavi, Abhijit
フォーマット: 論文
言語:English
主題:
Reinforcement learning.
Average reward.
Policy iteration.