AGVs Dispatching Using Multiple Cooperative Learing Agents

AGVs dispatching,one of the hot problems in FMS,has attracted widespread interest in recent years.It is hard to dynamically schedule AGVs with pre-designed rule because of the uncertaintty and dynamic nature of AGVs dispatching progress,so the AGVs system in this paper is treated as a cooperative learning multiagent system,in which each agent adopts multilevel decision method,which includes two level decisions:the option level and the action level,On the option level,an agent learns a policy to execute a subtask with the best response to the other AGVs‘ current options.On the action level,an agent learns an optimal policy of actions for achieving his planned option.The method is applied to a AGVs‘ dispatching simulation,and the performance of the AGVs system based on this method is verified.