Adaptive Swarm Behavior Acquisition Using a Neuro-Fuzzy Reinforcement Learning System

[1]  Kenji Doya,et al.  Metalearning and neuromodulation , 2002, Neural Networks.

[2]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[3]  Yasuaki Kuroe,et al.  Swarm Reinforcement Learning Algorithm Based on Exchanging Information among Agents , 2006 .

[4]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[5]  G. Di Caro,et al.  Ant colony optimization: a new meta-heuristic , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[6]  Lionel Jouffe,et al.  Fuzzy inference system learning by reinforcement methods , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[7]  Kunikazu Kobayashi,et al.  Adaptive swarm behavior acquisition by a neuro-fuzzy system and reinforcement learning algorithm , 2009, Int. J. Intell. Comput. Cybern..

[8]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[9]  Junichiro Yoshimoto,et al.  Control of exploitation-exploration meta-parameter in reinforcement learning , 2002, Neural Networks.

[10]  Kunikazu Kobayashi,et al.  A Neuro-fuzzy Learning System for Adaptive Swarm Behaviors Dealing with Continuous State Space , 2008, ICIC.

[11]  Xuesong Wang,et al.  A fuzzy Actor-Critic reinforcement learning network , 2007, Inf. Sci..

[12]  Long Cheng,et al.  Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Y. Kuroe,et al.  Swarm reinforcement learning algorithms based on Sarsa method , 2008, 2008 SICE Annual Conference.

[14]  Kunikazu Kobayashi,et al.  A reinforcement learning system for swarm behaviors , 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

[15]  Yishay Mansour,et al.  Learning Rates for Q-learning , 2004, J. Mach. Learn. Res..

[16]  Takahiro Sasaki,et al.  Reinforcement-learning agents with different temperature parameters explain the variety of human action-selection behavior in a Markov decision process task , 2009, Neurocomputing.

[17]  Kunikazu Kobayashi,et al.  An Improved Internal Model for Swarm Formation and Adaptive Swarm Behavior Acquisition , 2009, J. Circuits Syst. Comput..

[18]  Koji Nakano,et al.  A State Predictor Based Reinforcement Learning System , 2008 .

[19]  K. P. Sycara.  Multiagent systems : Special issue on agents , 1998 .

[20]  Majid Nili Ahmadabadi,et al.  Exploration and exploitation balance management in fuzzy reinforcement learning , 2010, Fuzzy Sets Syst..