Agent Organization Rule Generation Based on Reinforcement Learning

Agent organization is a flexible and effective way of solving multi agent system problems Within an agent organization, the rule plays an important role for reducing conflicts and improving resolution efficiency In this paper, mechanisms and the associated algorithms of agent organization rule generation based on reinforcement learning are given The experiment shows that the algorithms are more effective than the normal method The agent organization rule generation method proposed improves the work conducted by Zambonelli and Jennings