Experience based learning in policy control of multiagent system
Ariuna Damba, Shigeyoshi Watanabe · 2008
In this paper a method of simulated learning of policy control is proposed for dynamic multiagent system, where agent’s decision mechanism is represented as a function of agent’s past experience. The system of homogeneous agents with different sensor input and effector output is considered.