Abstract
In this paper, we propose a learning method for an agent to interact with other agents effectively. This method, MULA-C, improves efficiency of the learning, by clustering agents, and influences the learning experience of one agent to other agents which belong to the same cluster. Similarity among agents is evaluated by similarity among Q-values of agents. We give the detail explanation of learning method of MULA-C, and present the result of experiments which shows the effectiveness of MULA-C.
