Improving Multi agent Systems Based on Reinforcement Learning and Case Base Reasoning
In this paper, a new algorithm based on case base reasoning and reinforcement learning is proposed to increase the rate convergence of the Selfish Q-Learning algorithms in multi-agent systems. In the propose method, we investigate how making improved action selection in reinforcement learning (RL) algorithm. In the proposed method, the new combined model using case base reasoning systems and a new optimized function has been proposed to select the action, which has led to an increase in algorithms based on Selfish Q-learning. The algorithm mentioned has been used for solving the problem of cooperative Markovs games as one of the models of Markov based multi-agent systems. The results of experiments on two ground have shown that the proposed algorithm perform better than the existing algorithms in terms of speed and accuracy of reaching the optimal policy.
Keywords: Reinforcement learning, Selfish Q-learning, Case-base reasoning Systems, Multi-agent Systems, Cooperative Markov Games.
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ABOUT THE AUTHORS
Sara Esfandiari
received her BS degree in Computer Engineering from the azad University, Tehran, Iran., in 2006 and MS degree in Computer Engineering in 2011 from the azad University, Qazvin, Iran. Her research interests include Learning systems, multi agent systems, multi agent learning, Data Mining, parallel algorithms.
Behrooz Masoumi
received his BS and MS degrees in Computer Engineering in 1995 and 1998, respectively. He also received his PhD degrees in Computer Engineering from the Science and Research University, Tehran, Iran., in 2011. He joined the faculty of Computer and IT Engineering Department at Qazvin Azad University, Qazvin, Iran, in 1998. His research interests include learning systems, multi-agent systems, multi-agent learning, and soft computing.
Mohammadreza Meybodi
received his BS and MS degrees in Economics from the Shahid Beheshti University in Iran, in 1973 and 1977, respectively. He also received his MS and PhD degrees in Computer Science from the Oklahoma University, U.S.A., in 1980 and 1983, respectively. Currently he is a Full Professor in the Computer Engineering Department, Amirkabir University of Technology, Tehran, Iran. Prior to his current position, he worked from 1983 to 1985 as an Assistant Professor at Western Michigan University, and from 1985 to 1991 as an Associate Professor at Ohio University, U.S.A. His research interests include channel management in cellular networks, learning systems, parallel algorithms, soft computing, and software development.
Abdolkarim Niazi
is currently PhD Student in Mechanical Engineering-Manufacturing engineering at Technical University of Malaysia from 2010 up to now. His research interests include Condition monitoring, Tools Condition monitoring, Tool wear and tool vibration, Advance and Automated Manufacturing Systems, Artificial Neural Networks.
Sara Esfandiari
received her BS degree in Computer Engineering from the azad University, Tehran, Iran., in 2006 and MS degree in Computer Engineering in 2011 from the azad University, Qazvin, Iran. Her research interests include Learning systems, multi agent systems, multi agent learning, Data Mining, parallel algorithms.
Behrooz Masoumi
received his BS and MS degrees in Computer Engineering in 1995 and 1998, respectively. He also received his PhD degrees in Computer Engineering from the Science and Research University, Tehran, Iran., in 2011. He joined the faculty of Computer and IT Engineering Department at Qazvin Azad University, Qazvin, Iran, in 1998. His research interests include learning systems, multi-agent systems, multi-agent learning, and soft computing.
Mohammadreza Meybodi
received his BS and MS degrees in Economics from the Shahid Beheshti University in Iran, in 1973 and 1977, respectively. He also received his MS and PhD degrees in Computer Science from the Oklahoma University, U.S.A., in 1980 and 1983, respectively. Currently he is a Full Professor in the Computer Engineering Department, Amirkabir University of Technology, Tehran, Iran. Prior to his current position, he worked from 1983 to 1985 as an Assistant Professor at Western Michigan University, and from 1985 to 1991 as an Associate Professor at Ohio University, U.S.A. His research interests include channel management in cellular networks, learning systems, parallel algorithms, soft computing, and software development.
Abdolkarim Niazi
is currently PhD Student in Mechanical Engineering-Manufacturing engineering at Technical University of Malaysia from 2010 up to now. His research interests include Condition monitoring, Tools Condition monitoring, Tool wear and tool vibration, Advance and Automated Manufacturing Systems, Artificial Neural Networks.
