Multiagent learning towards RoboCup

This article describes the issues in multiagent learning towards RoboCup,1≈3) especially for the real robot leagues. First, the review of the issue in the context of the related area is given, then related works from several viewpoints are reviewed. Next, our approach towards RoboCup Initiative is introduced and finally future issues are given.

[1]  Hiroaki Kitano,et al.  RoboCup-99: Robot Soccer World Cup III , 2003, Lecture Notes in Computer Science.

[2]  Wallace E. Larimore,et al.  Canonical variate analysis in identification, filtering, and adaptive control , 1990, 29th IEEE Conference on Decision and Control.

[3]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[4]  Yuichiro Anzai,et al.  Reducing communication load on contract net by case-based reasoning:extension with directed contract , 1995 .

[5]  Michael L. Littman,et al.  Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.

[6]  Alan H. Bond,et al.  Distributed Artificial Intelligence , 1988 .

[7]  Maja J. Matarić,et al.  Learning to Use Selective Attention and Short-Term Memory in Sequential Tasks , 1996 .

[8]  James A. Hendler,et al.  Co-evolving Soccer Softbot Team Coordination with Genetic Programming , 1997, RoboCup.

[9]  Pentti Kanerva,et al.  Sparse distributed memory and related models , 1993 .

[10]  Leslie Pack Kaelbling,et al.  Learning in embedded systems , 1993 .

[11]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[12]  Mario Tokoro,et al.  An Adaptive Architecture for Modular Q-Learning , 1997, IJCAI.

[13]  Marco Colombetti,et al.  Robot Shaping: Developing Autonomous Agents Through Learning , 1994, Artif. Intell..

[14]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[15]  H. Akaike.  A new look at the statistical model identification , 1974 .

[16]  Yasuo Kuniyoshi.  Behavior Matching by Observation for Multi-Robot Cooperation , 1996 .

[17]  Sandip Sen,et al.  Learning to Coordinate without Sharing Information , 1994, AAAI.

[18]  Luc Steels.  Structural coupling of cognitive memories through adaptive language games , 1998 .

[19]  Michael P. Wellman,et al.  Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm , 1998, ICML.

[20]  Gillian M. Hayes,et al.  Imitative Learning Mechanisms in Robots and Humans , 1996 .

[21]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[22]  Luc Steels,et al.  Grounding adaptive language games in robotic agents , 1997 .

[23]  D. Floreano,et al.  Adaptive Behavior in Competing Co-Evolving Species , 2000 .

[24]  Pattie Maes,et al.  Co-evolution of Pursuit and Evasion II: Simulation Methods and Results , 1996 .

[25]  Masayuki Inaba,et al.  Learning by watching: extracting reusable task knowledge from visual observation of human performance , 1994, IEEE Trans. Robotics Autom..

[26]  Randall Davis,et al.  Frameworks for Cooperation in Distributed Problem Solving , 1988, IEEE Transactions on Systems, Man, and Cybernetics.

[27]  Masahiko Yachida,et al.  Multi-agent reinforcement learning with adaptive mimetism , 1996, Proceedings 1996 IEEE Conference on Emerging Technologies and Factory Automation. ETFA '96.

[28]  Steven D. Whitehead,et al.  Complexity and Cooperation in Q-Learning , 1991, ML.

[29]  Rajesh P. N. Rao,et al.  Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory , 1998, Machine Learning.

[30]  Minoru Asada,et al.  Behavior coordination for a mobile robot using modular reinforcement learning , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[31]  Tom M. Mitchell,et al.  Reinforcement learning with hidden states , 1993 .

[32]  Manuela M. Veloso,et al.  Team-partitioned, opaque-transition reinforcement learning , 1999, AGENTS '99.

[33]  Leo H. Chiang,et al.  Canonical Variate Analysis , 2000 .

[34]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[35]  François Michaud,et al.  Learning from History for Behavior-Based Mobile Robots in Non-Stationary Conditions , 1998, Machine Learning.

[36]  John R. Koza,et al.  Genetic programming 2 - automatic discovery of reusable programs , 1994, Complex adaptive systems.

[37]  Minoru Asada,et al.  Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning and Development , 1999, Artif. Intell..