Shahab Shamshirband - Islamic Azad University
Saeed Setayeshi - Amirkabir University
Mahmoud Naghibzadeh - Ferdowsi University
kimia Rezaei kalantari - Islamic Azad University

The single traffic signal control agent improves its control ability with the Multiagentslearning method. This paper proposes a new cooperative learning method; called weighted strategy sharing (WSS) is presented. In this method, each agent measures the expertness of its team-mates and assigns a weight to their knowledge and learns from them accordingly. The presented methods are tested on three traffic lights. Also, the effect of the communication noise, as a source of uncertainty, on the cooperative learning method is studied. Moreover, the Q-table of one of the cooperative agents is changed randomly and its effects on the presented methods are examined. Results using cooperative traffic agents are compared to results of control simulations where non-cooperative agents were deployed. The result indicates that the new coordination method proposed in this paper is effective.

Multiagents, Cooperative learning, expertness, multi-agent systems, Q-learning