An agent reinforcement learning model based on neural networks

Authors:
Liang Gui Tang;Bo An;Dai Jie Cheng
Affiliations:
College of Computer Science, Chongqing University, Chongqing, P.R. China and College of Computer Science, Chongqing Technology and Business University, Chongqing, P.R.China;Dept. of Computer Science, University of Massachusetts, Amherst;College of Computer Science, Chongqing University, Chongqing, P.R. China
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

Citing 8
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Abstract

This paper thoroughly analyzes the transfer and construction of the state-action space of the agent decision-making process, discusses the optimal strategy of agent's action selection based on Markov decision-making process, designs a neural networks model for the agent reinforcement learning, and designs the agent reinforcement learning based on neural networks. By the simulation experiment of agent's bid price in Multi-Agent Electronic Commerce System, validated the Agent Reinforcement Learning Algorithm Based on Neural Networks has very good performance and the action impending ability.