2024 : 4 : 12
Abolghasem Daeichian

Abolghasem Daeichian

Academic rank: Associate Professor
ORCID: https://orcid.org/0000-0002-6318-579X
Education: PhD.
ScopusId: 55916844500
Faculty: Engineering
Address: Arak University
Phone: 08632625436


Fuzzy Q-Learning-Based Multi-agent System for Intelligent Traffic Control by a Game Theory Approach
Traffic control, Multi-agent system, Game theory, Fuzzy Q-learning
Journal Arabian Journal for Science and Engineering
Researchers Abolghasem Daeichian ، Amir Haghani


This paper introduces a multi-agent approach to adjust traffic lights based on traffic situation in order to reduce average delay time. In the traffic model, lights of each intersection are controlled by an autonomous agent. Since decision of each agent affects neighbor agents, this approach creates a classical non-stationary environment. Thus, each agent not only needs to learn from the past experience but also has to consider decision of neighbors to overcome dynamic changes of the traffic network. Fuzzy Q-learning and Game theory are employed to make policy based on previous experiences and decision of neighbor agents. Simulation results illustrate the advantage of the proposed method over fixed time, fuzzy, Q-learning and fuzzy Q-learning control methods.