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.KeywordsNeural Network ModelReinforcement LearnAgent ReinforcementContinuous State SpaceLearn UnitThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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