Abstract
Distributed Artificial Intelligence (DAI) has existed as a subfield of AI for less than two decades. DAI is concerned with systems that consist of multiple independent entities that interact in a domain. Traditionally, DAI has been divided into two sub-disciplines: Distributed Problem Solving (DPS) focuses on the information management aspects of systems with several components working together towards a common goal; Multiagent Systems (MAS) deals with behavior management in collections of several independent entities, or agents. This survey of MAS is intended to serve as an introduction to the field and as an organizational framework. A series of general multiagent scenarios are presented. For each scenario, the issues that arise are described along with a sampling of the techniques that exist to deal with them. The presented techniques are not exhaustive, but they highlight how multiagent systems can be and have been used to build complex systems. When options exist, the techniques presented are biased towards machine learning approaches. Additional opportunities for applying machine learning to MAS are highlighted and robotic soccer is presented as an appropriate test bed for MAS. This survey does not focus exclusively on robotic systems. However, we believe that much of the prior research in non-robotic MAS is relevant to robotic MAS, and we explicitly discuss several robotic MAS, including all of those presented in this issue.
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AAAI. 1995. Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, CA, AAAI Press. Victor Lessor-General Chair.
Achim, S., Stone, P., and Veloso, M. 1996. Building a dedicated robotic soccer system. In Proceedings of the IROS-96 Workshop on RoboCup, Osaka, Japan, pp. 41–48.
Andou, T. 1998. Refinement of soccer agents' positions using reinforcement learning. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlins, pp. 373–388.
Andre, E., Herzog, G., and Rist, T. 1988. On the simultaneous interpretation of real world image sequences and their natural language description: The system soccer. In Proc.of the 8th ECAI, Munich, pp. 449–454.
Andre, E., Herzog, G., and Rist, T. 1998. Generating multimedia presentations for RoboCup soccer games. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 200–215.
Andre, D. and Teller, A. 1999. Evolving team Darwin United. In RoboCup-98: Robot SoccerWorld Cup II, M. Asada and H. Kitano (Eds.), Springer Verlag: Berlin.
Arora, N. and Sen, S. 1996. Resolving social dilemmas using genetic algorithms. In Adaptation, Coevolution and Learning in Multiagent Systems: Papers from the 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI Press, pp. 1–5. AAAI Technical Report SS-96-01.
Asada, M. and Kitano, H. (Eds.) 1999. RoboCup-98: Robot Soccer World Cup II, Springer Verlag: Berlin. Lecture Notes in Artificial Intelligence, vol. 1604.
Asada, M., Noda, S., and Hosoda, K. 1996. Action-based sensor space categorization for robot learning. In Proc.of IEEE/RSJ International Conference on Intelligent Robots and Systems 1996 (IROS' 96), pp. 1502–1509.
Asada, M., Noda, S., Tawaratsumida, S., and Hosoda, K. 1994a. Purposive behavior acquisition on a real robot by vision-based reinforcement learning. In Proc.of MLC-COLT (Machine Learning Confernce and Computer Learning Theory) Workshop on Robot Learning, pp. 1–9.
Asada, M., Uchibe, E., Noda, S., Tawaratsumida, S., and Hosoda, K. 1994b. Coordination of multiple behaviors acquired by visionbased reinforcement learning. In Proc.of IEEE/RSJ/GI International Conference on Intelligent Robots and Systems 1994, pp. 917–924.
Balch, T. 1998. Behavioral diversity in learning robot teams. PhD Thesis, College of Computing, Georgia Institute of Technology.
Balch, T. 2000. Social entropy: An information theoretic measure of robot team diversity. Autonomous Robots, 8(3):1–25.
Balch, T. and Arkin, R.C. 1994. Communication in reactive multiagent robotic systems. Autonomous Robots, 1(1).
Balch, T. and Arkin, R.C. 1995. Motor schema-based formation control for multiagent robot teams. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 10–16.
Barbuceanu, M. and Fox, M.S. 1995. COOL: A language for describing coordination in multi agent systems. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 17–24.
Barman, R.A., Kingdon, S.J., Little, J.J., Mackworth, A.K., Pai, D.K., Sahota, M., Wilkinson, H., and Zhang, Y. 1993. DYNAMO: Real-time experiments with multiple mobile robots. In Intelligent Vehicles Symposium, Tokyo, pp. 261–266.
Beckers, R., Holland, E., and Deneubourg, J.L. 1994. From local actions to global tasks: Stigmergy and collective robotics. In Artifical Life IV: Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems, R. Brooks and P. Maes (Eds.), MIT Press, pp. 181–189.
Benda, M., Jagannathan, V., and Dodhiawala, R. 1986. On optimal cooperation of knowledge sources—an empirical investigation. Technical Report BCS-G2010-28, Boeing Advanced Technology Center, Boeing Computing Services, Seattle, Washington.
Binsted, K. 1999. Character design for soccer commentary. In RoboCup-98: Robot SoccerWorld Cup II, M. Asada and H. Kitano (Eds.), Springer Verlag: Berlin.
Bond, A.H. and Gasser, L. 1988. An analysis of problems and research in DAI. In Readings in Distributed Artificial Intelligence, A.H. Bond and L. Gasser (Eds.), Morgan Kaufmann Publishers: San Mateo, CA, pp. 3–35.
Bowling, M. and Veloso, M. 1999. Motion control in dynamic multirobot environments. In Proceedings of The 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA'99), Monterrey.
Bull, L., Fogarty, T.C., and Snaith, M. 1995. Evolution in multi-agent systems: Evolving communicating classifier systems for gait in a quadrupedal robot. In Proceedings of the Sixth International Conference on Genetic Algorithms, S. Forrest (Ed.), Morgan Kaufman: San Mateo, CA, pp. 382–388.
Cao, Y.U., Fukunaga, A.S., and Kahng, A.B. 1997. Cooperative mobile robotics: Antecedents and directions. Autonomous Robots, 4:7–27.
Castaño, A., Shen, W.-M., and Will, P. 2000. CONRO: Towards deployable robots with inter-robot metamorphic capabilities. Autonomous Robots, 8(3):309–324.
Castelfranchi, C. 1995. Commitments: From individual intentions to groups and organizations. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 41–48.
Ch'ng, S. and Padgham, L. 1998. From roles to teamwork: A framework and architecture. Applied Artificial Intelligence, 12:211–232.
rCheng, G. and Zelinsky. A. 1998. Real-time vision processing for a soccer playing mobile robot. In RoboCup-97: Robot SoccerWorld Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 144–155.
Clouse, J.A. 1996. Learning from an automated training agent. In Adaptation and Learning in Multiagent Systems, G. Weiß and S. Sen (Eds.), Springer Verlag: Berlin.
Cohen, P.R. and Levesque, H.J. 1995. Communicative actions for artificial agents. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 65–72.
Coradeschi, S. and Karlsson, L. 1998. A role-based decisionmechanism for teams of reactive and coordinating agents. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 112–122.
Dautenhahn, K. 1995. Getting to know each other—artificial social intelligence for autonomous robots. Robotics and Autonomous Systems, 16:333–356.
de la, Rosa, J.Ll. Oller, A., Vehi, J., and Puyol, J. 1997. Soccer team based on agent-oriented programming. Robotics and Autonomous Systems, 21(2):161–176.
Decker, K.S. 1987. Distributed problem solving: A survey. IEEE Transactions on Systems, Man, and Cybernetics, 17(5):729–740.
Decker, K.S. 1995. Environment centered analysis and design of coordination mechanisms. PhD Thesis, University of Massachusetts.
Decker, K.S. 1996a. Distributed artificial intelligence testbeds. In Foundations of Distributed Artificial Intelligence, G.M.P. O'Hare and N.R. Jennings (Eds.), Wiley Interscience, pp. 119–138.
Decker, K.S. 1996b. Personal correspondence.
Decker, K.S. 1996c. Task environment centered simulation. In Simulating Organizations: Computational Models of Institutions and Groups, M. Prietula, K. Carley, and L. Gasser (Eds.), AAAI Press/MIT Press.
Decker, K.S. and Lesser, V.R. 1995. Designing a family of coordination algorithms. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 73–80.
Drogoul, A. and Collinot, A. 1998. Applying an agent-oriented methodology to the design of artificial organizations: Acase study in robotic soccer. Autonomous Agents and Multi-Agent Systems, 1(1):113–129.
Dudek, G., Jenkin, M.R.M., Milios, E., and Wilkes, D. 1996. A taxonomy for multi-agent robotics. Autonomous Robots, 3(4):375–397.
Durfee, E.H. 1992. What your computer really needs to know, you learned in kindergarten. In Proceedings of the Tenth National Conference on Artificial Intelligence, Philadelphia, PA, Morgan Kaufman.
Durfee, E.H. 1995. Blissful ignorance: Knowing just enough to coordinate well. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 406–413.
Durfee, E.H., Lesser, V.R., and Corkill, D.D. 1989. Trends in cooperative distributed problem solving. IEEE Transactions on Knowledge and Data Engineering, 1(1):63–83.
Fenster, M., Kraus, S., and Rosenschein, J.S. 1995. Coordination without communication: Experimental validation of focal point techniques. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 102–108.
Ferguson, I.A. and Karakoulas, G.J. 1996. Multiagent learning and adaptation in an information filtering market. In Adaptation, Coevolution and Learning in Multiagent Systems: Papers from the 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI Press, pp. 28–32. AAAI Technical Report SS-96-01.
Finin, T., McKay, D., Fritzson, R., and McEntire, R. 1994. KQML: An information and knowledge exchange protocol. In Knowledge Building and Knowledge Sharing, K. Fuchi and T. Yokoi (Eds.), Ohmsha and IOS Press.
Ford, R., Boutilier, C., and Kanazawa, K. 1994. Exploiting natural structure in reinforcement learning: Experience in robot soccerplaying. Unpublished Manuscript.
Fox, D., Burgard, W., Kruppa, H., and Thrun, S. 2000. Aprobabilistic approach to collaborative multi-robot localization. Autonomous Robots, 8(3):325–344.
rFujita, M. and Kageyama, K. 1997. An open architecture for robot entertainment. In Proceedings of the First International Conference on Autonomous Agents, Marina del Rey, CA, pp. 435–442.
Genesereth, M.R. and Fikes, R.E. 1992. Knowledge interchange format, version 3.0 reference manual. Technical Report Logic-92-1, Computer Science Department, Stanford University.
Glance, N.S. and Hogg, T. 1995. Dilemmas in computational societies. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 117–124.
Goldman, C. and Rosenschein, J. 1994. Emergent coordination through the use of cooperative state-changing rules. In Proceedings of the Twelfth National Conference on Artificial Intelligence, Philadelphia, PA, Morgan Kaufman, pp. 408–413.
Grabowski, R., Navarro-Serment, L.E., Paredis, C.J.J., and Khosla, P.K. 2000. Heterogeneous teams of modular robots for mapping and exploration. Autonomous Robots, 8(3):293–308.
Grand, S. and Cliff, D. 1998. Creatures: Entertainment software agents with artificial life. Autonomous Agents and Multi-Agent Systems, 1(1):39–58.
Grefenstette, J. and Daley, R. 1996. Methods for competitive and cooperative co-evolution. In Adaptation, Coevolution and Learning in Multiagent Systems: Papers from the 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI Press, pp. 45–50, AAAI Technical Report SS-96-01.
Gutmann, J.-S., Hattzack, W., Herrmann, I., Nebel, B., Rittinger, F., Topor, A., Weigel, T., and Welsch, B. 1998. The CS Freiburg team. In Proceedings of the Second RoboCupWorkshop, M. Asada (Ed.), Paris, France, pp. 451–458.
Haddadi, A. 1995. Towards a pragmatic theory of interactions. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 133–139.
Han, W.-G., Baek, S.-M., Kuc, T.-Y., and Kwan, S.K. 1996. Path planning of visual-served multiple mobile robots using the genetic algorithms. In Proceedings of the Micro-Robot World Cup Soccer Tournament, Taejon, Korea, IEEE Robotics and Automation Society, pp. 57–63.
Han, K. and Veloso, M. 1998. Reactive visual control of multiple non-holonomic robotic agents. In Proceedings of the International Conference on Robotics and Automation, Leuven, Belgium.
Hayes-Roth, B., Brownston, L., and van Gent, R. 1995. Multiagent collaboration in directed improvisation. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 148–154.
Haynes, T. and Sen, S. 1998. Evolving behavioral strategies in predators and prey. In Adaptation and Learning in Multiagent Systems, G. Weiß and S. Sen (Eds.), Springer Verlag: Berlin, pp. 113–126.
Haynes, T. and Sen, S. 1998. Learning cases to resolve conflicts and improve group behavior. International Journal of Human-Computer Studies, 48:31–49.
Haynes, T., Wainwright, R., Sen, S., and Schoenefeld, D. 1995. Strongly typed genetic programming in evolving cooperation strategies. In Proceedings of the Sixth International Conference on Genetic Algorithms, S. Forrest (Ed.), Morgan Kaufman: San Mateo, CA, pp. 271–278.
Hirai, K. 1997. Development of the Honda humanoid robot. Presentation at the CMU Robotics Institute Seminar. At URL http://www.honda.co.jp/home/hpr/e news/robot/.
Holland, O.E. 1996. Multiagent systems: Lessons from social insects and collective robotics. In Adaptation, Coevolution and Learning in Multiagent Systems: Papers fromthe 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI Press, pp. 57–62. AAAI Technical Report SS-96-01.
Hong, S.-G., Eom, T.-D., Jeong, Il.-K., Choi, C., Shin, J.-H. and Lee, J.-J. 1996. Development of soccer-playing robots: Control, cooperation, and strategy. In Proceedings of the Micro-Robot World Cup Soccer Tournament, Taejon, Korea, IEEE Robotics and Automation Society, pp. 134–141.
Hsia, T.C. and Soderstrand, M. 1996. Development of a micro robot system for playing soccer games. In Proceedings of the Micro-RobotWorld Cup Soccer Tournament, Taejon, Korea, IEEE Robotics and Automation Society, pp. 149–152.
Huber, M.J. and Durfee, E.H. 1995. Deciding when to commit to action during observation-based coordination. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 163–170.
Huberman, B. and Clearwater, S.H. 1995. A multi-agent system for controlling building environments. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 171–176.
Inoue, N. and Wilkin, S. 1997. Learning system for the formation and the pass-play. Presented at the Poster Session of the IROS-96 Workshop on RoboCup.
Jennings, N.R. and Wittig, T. 1992. Archon: Theory and practice. In Distributed Artificial Intelligence: Theory and Praxis, N.M. Avouris and L. Gasser (Eds.), Kluwer Academic Press, pp. 179–195.
Jung, D. and Zelinsky, A. 2000. Grounded symbolic communication between heterogeneous cooperating robots. Autonomous Robots, 8(3):269–292.
Kaelbling, L.P., Littman, M.L., and Moore, A.W. 1996. Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4:237–285.
Kim, J.-H. (Ed.). 1996. Proceedings of the Micro-Robot World Cup Soccer Tournament, Taejon, Korea.
Kim, D.-Y. and Chung, M.J. 1996. Path planning for multi-mobile robots in the dynamic environment. In Proceedings of the Micro-Robot World Cup Soccer Tournament, Taejon, Korea, IEEE Robotics and Automation Society, pp. 127–132.
Kim, K.-H., Ko, K.-W., Kim, J.-G., Lee, S.-H., and Cho, H.S. 1996. Multiple micro robots playing robot soccer game. In Proceedings of the Micro-RobotWorld Cup Soccer Tournament, Taejon, Korea, IEEE Robotics and Automation Society, pp. 38–43.
Kitano, H. (Ed.). 1996. Proceedings of the IROS-96 Workshop on RoboCup, Osaka, Japan.
Kitano, H. (Ed.). 1998. RoboCup-97: Robot Soccer World Cup I, Springer Verlag: Berlin.
Kitano, H., Asada, M., Noda, I., and Matsubara, H. 1998. RoboCup: Robot world cup. Crossroads, 4.3.
Kitano, H., Kuniyoshi, Y., Noda, I., Asada, M., Matsubara, H., and Osawa, E. 1997a. RoboCup: A challenge problem for AI. AI Magazine, 18(1):73–85.
Kitano, H., Tambe, M., Stone, P., Veloso, M., Coradeschi, S. Osawa, E., Matsubara, H., Noda, I., and Asada, M. 1997b. The RoboCup synthetic agent challenge 97. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, San Francisco, CA, Morgan Kaufmann, pp. 24–29.
Korf, R.E. 1992. A simple solution to pursuit games. In Working Papers of the 11th InternationalWorkshop on Distributed Artificial Intelligence, pp. 183–194.
Koza, J.R. 1992. Genetic Programming, MIT Press.
Lesser, V.R. 1995. Multiagent systems: An emerging subdiscipline of AI. ACM Computing Surveys, 27(3):340–342.
Lesser, V. 1998. Reflections on the nature of multi-agent coordination and its implications for an agent architecture. Autonomous Agents and Multi-Agent Systems, 1(1):89–112.
rLevy, R. and Rosenschein, J.S. 1992. A game theoretic approach to the pursuit problem. In Working Papers of the 11th International Workshop on Distributed Artificial Intelligence, pp. 195–213.
Littman, M.L. 1994. Markov games as a framework for multi-agent reinforcement learning. In Proceedings of the Eleventh International Conference on Machine Learning, San Mateo, CA, Morgan Kaufman, pp. 157–163.
Luke, S., Hohn, C., Farris, J., Jackson, G., and Hendler, J. 1998. Co-evolving soccer softbot team coordination with genetic programming. In RoboCup-97: Robot SoccerWorld Cup I,, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 398–411.
Lux, A. and Steiner, D. 1995. Understanding cooperation: Anagent's perspective. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 261–268.
Mackworth, A.K. 1993. On seeing robots. In Computer Vision: Systems, Theory, and Applications, A. Basu and X. Li (Eds.), World Scientific Press: Singapore, pp. 1–13.
Mataric, M.J. 1994a. Interaction and intelligent behavior. MIT EECS PhD Thesis AITR-1495, MIT AI Lab.
Mataric, M.J. 1994b. Learning to behave socially. In Third International Conference on Simulation of Adaptive Behavior.
Matsubara, H., Frank, I., Tanaka-Ishii, K., Noda, I., Nakashima, H., and Hasida, K. 1999. Automatic soccer commentary and RoboCup. In RoboCup-98: Robot SoccerWorld Cup II, M. Asada and H. Kitano (Eds.), Springer Verlag: Berlin.
Matsubara, H., Noda, I., and Hiraki, K. 1996. Learning of cooperative actions in multi-agent systems: a case study of pass play in soccer. In Adaptation, Coevolution and Learning in Multiagent Systems: Papers from the 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI Press, pp. 63–67. AAAI Technical Report SS-96-01.
Matsumoto, A. and Nagai, H. 1998. Decision making by the characteristics and the interaction in multi-agent robotics soccer. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 132–143.
Matsuyama, T. 1997. Cooperative distributed vision. In Proceedings of the First International Workshop on Cooperative Distributed Vision, Kyoto, Japan.
Minsky, M.L. 1988. The Society of Mind, Simon & Schuster.
Mizuno, H., Kourogi, M., Kawamoto, Y., and Muraoka, Y. 1998. A method applied for soccer's behaviors using proper feedback and feedforward control. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 156–167.
Mizuno, H., Kourogi, M., and Muraoka, Y. 1996. Building shoobot possible to dribble and shoot. In Proceedings of the IROS-96Workshop on RoboCup.
Mor, Y. and Rosenschein, J. 1995. Time and the prisoner's dilemma. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 276–282.
Moukas, A. and Maes, P. 1997. Trafficopter: A distributed collection system for traffic information. At URL http://trafficopter. www.media.mit.edu/projects/trafficopter/.
Nadella, R. and Sen, S. 1997. Correlating internal parameters and external performance: Learning soccer agents. In Distributed Artificial Intelligence Meets Machine Learning, G. Weiß (Ed.), Springer-Verlag, pp. 137–150.
Nakashima, H., Noda, I., and Ohsawa, I. 1995. Organic programming for multi-agents. In Proceedings of the First International Conference on Multi-Agent Systems, V. Lesser (Ed.), MIT Press: San Francisco, CA, p. 459.
Noda, I. 1998. Team GAMMA: Agent programming on gaea. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 500–507.
Noda, I., Matsubara, H., Hiraki, K., and Frank, I. 1998. Soccer server: A tool for research on multiagent systems. Applied Artificial Intelligence, 12:233–250.
Osawa, E.-I. 1995. A metalevel coordination strategy for reactive cooperative planning. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 297–303.
Parker, L.E. 1994. Heterogeneous multi-robot cooperation. PhD Thesis, Massachusetts Institute of Technology.
Parker, L.E. 2000. Life-long adaptation in heterogeneous multi-robot teams: Response to continual variation in individual robot performance. Autonomous Robots, 8(3):239–267.
Van Dyke Parunak, H. 1996. Applications of distributed artificial intelligence in industry. In Foundations of Distributed Artificial Intelligence, G.M.P. O'Hare and N.R. Jennings (Eds.), Wiley Interscience, pp. 139–164.
Van Dyke Parunak, H., Ward, A., and Sauter, J. 1998. A systematic market approach to distributed constraint problems. In Proceedings of the Third International Conference on Multi-Agent Systems, pp. 455–456.
Permpoontanalarp, Y. 1995. Generalised proof-theory for multiagent autoepistemic reasoning. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 304–311.
Pormerleau, D.A. 1993. Neural NetworkPerception for Mobile Robot Guidance, Kluwer Academic Publishers.
Potter, M.A., De Jong, K.A., and Grefenstette, J.J. 1995. A coevolutionary approach to learning sequential decision rules. In Proceedings of the Sixth International Conference on Genetic Algorithms, S. Forrest (Ed.), Morgan Kaufman: San Mateo, CA, pp. 366–372.
Prasad, M.V.N., Lander, S.E., and Lesser, V.R. 1998. Learning organizational roles for negotiated search in a multiagent system. International Journal of Human-Computer Studies, 48:51–67.
Price, A., Jennings, A., and Kneen, J. 1998. RoboCup97: An omnidirectional perspective. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 320–332. Proceedings of the 10th International Workshop on Distributed Artificial Intelligence, Bandera, Texas, October 1990.
Rao, A.S. and Georgeff, M.P. 1995. BDI agents: From theory to practice. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 312–319.
Ridley, M. 1997. The Origins of Virtue: Human Instincts and the Evolution of Cooperation, Viking Press.
Riekki, J. and Roening, J. 1998. Playing soccer by modifying and combining primitive reactions. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 74–87.
Rosenschein, J.S. and Zlotkin, G. 1994. Rules of Encounter, MIT Press.
Rosin, C.D. and Belew, R.K. 1995. Methods for competitive coevolution: Finding opponentsworth beating. In Proceedings of the Sixth International Conference on Genetic Algorithms, S. Forrest (Ed.), Morgan Kaufman: San Mateo, CA, pp. 373–380.
Russell, S.J. and Norvig, P. 1995. Artificial Intelligence: A Modern Approach, Prentice Hall: Englewood Cliffs, NJ.
Sahota, M.K. 1994. Reactive deliberation: An architecture for realtime intelligent control in dynamic environments. In Proceedings of the Twelfth National Conference on Artificial Intelligence, pp. 1303–1308.
Sahota, M.K. 1996. Dynasim user guide. At URL http://www. cs.ubc.ca/nest/lci/soccer.
Sahota, M.K., Mackworth, A.K., Barman, R.A., and Kingdon, S.J. 1995. Real-time control of soccer-playing robots using off-board vision: The Dynamite testbed. In IEEE International Conference on Systems, Man, and Cybernetics, pp. 3690–3663.
Sanchez, J.A., Azevedo, F.S., and Leggett, J.J. 1995. Paragente: Exploring the issues in agent-based user interfaces. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 320–327.
Sandholm, T.W. and Crites, R.H. 1996. On multiagent Q-learning in a semi-competitive domain. In Adaptation and Learning in Multiagent Systems, G. Weiß and S. Sen (Eds.), SpringerVerlag: Berlin.
Sandholm, T. and Lesser, V. 1995. Coalition formation among bounded rational agents. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Los Angeles, CA, Morgan Kaufman, pp. 662–669.
Sandholm, T. and Lesser, V. 1995. Issues in automated negotiation and electronic commerce: Extending the contract net framework. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 328–335.
Sandholm, T. and Lesser, V. 1996. Advantages of a leveled commitment contracting protocol. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, Menlo Park, California, AAAI Press, pp. 126–133.
Sargent, R., Bailey, B., Witty, C., and Wright, A. 1997. Dynamic object capture using fast vision tracking. AI Magazine, 18(1):65–72.
Scerri, P. 1998. A multi-layered behavior based system for controlling RoboCup agents. In RoboCup-97: Robot SoccerWorld Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 467–474.
Schaerf, A., Shoham, Y., and Tennenholtz, M. 1995. Adaptive load balancing: A study in multi-agent learning. Journal of Artificial Intelligence Research, 2:475–500.
Schmidhuber, J. 1996. A general method for multi-agent reinforcement learning in unrestricted environments. In Adaptation, Coevolution and Learning in Multiagent Systems: Papers from the 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI Press, pp. 84–87. AAAI Technical Report SS-96-01.
Sen, S. (Ed.). 1996. Adaptation, Coevolution and Learning in Multiagent Systems: Papers from the 1996 AAAI Spring Symposium, Menlo Park, CA, AAAI, AAAI Press. AAAI Technical Report SS-96-01.
Sen, S., Arora, N., and Roychowdhury, S. 1998. Using limited information to enhance group stabilitys. International Journal of Human-Computer Studies, 48:69–82.
Shehory, O. and Kraus, S. 1995. Task allocation via coalition formation among autonomous agents. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Los Angeles, CA, Morgan Kaufman, pp. 655–661.
Shen, W.-M., Adibi, J., Adobbati, R., Cho, B., Erdem, A., Moradi, H., Salemi, B., and Tejada, S. 1998. Building integrated mobile robots for soccer competition. In Proceedings of the International Conference on Robotics and Automation.
Shim, H.-S., Jung, M.-J., Kim, H.-S., Choi, I.-H., Han, W.-S., and Kim, J.-H. 1996. Designing distributed control architecture for cooperative multiagent systems. In Proceedings of the Micro-Robot World Cup Soccer Tournament, Taejon, Korea, IEEE Robotics and Automation Society, pp. 19–25.
Shinjoh, A. 1998. RoboCup-3D: The construction of intelligent navigation system. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 188–199.
Shoham, Y. 1990. Agent-oriented programming. Technical Report CS-1335-90, Computer Science Dept., Stanford University.
Sichman, J.S. and Demazeau, Y. 1995. Exploiting social reasoning to deal with agency level inconistency. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 352–359.
Smith, R.G. 1980. The contract net protocol: High-level communication and control in a distributed problem solver. IEEE Transactions on Computers, C-29(12):1104–1113.
Stephens, L.M. and Merx, M.B. 1990. The effect of agent control strategy on the performance of a dai pursuit problem. In Proceedings of the 10th International Workshop on Distributed Artificial Intelligence, Bandera, Texas.
Stone, P. 2000. Layered learning in multiagent systems: A winning approach to robotic soccer. Intelligent Robotics and Autonomous Agents, MIT Press.
Stone, P. and Veloso, M. 1996. Beating a defender in robotic soccer: Memory-based learning of a continuous function. In Advances in Neural Information Processing Systems 8, D.S. Touretzky, M.C. Mozer, and M.E. Hasselmo (Eds.), MIT Press: Cambridge, MA, pp. 896–902.
Stone, P. and Veloso, M. 1996. Using machine learning in the soccer server. In Proceedings of the IROS-96 Workshop on RoboCups, Osaka, Japan, pp. 19–27.
Stone, P. and Veloso, M. 1998. Towards collaborative and adversarial learning: A case study in robotic soccer. International Journal of Human-Computer Studies, 48(1):83–104.
rStone, P. and Veloso, M. 1999. Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork. Artificial Intelligence, 110(2):241–273.
Stone, P., Veloso, M., and Riley, P. 1999. The CMUnited-98 champion simulator team. In RoboCup-98: Robot Soccer World Cup II. M. Asada and H. Kitano (Eds.), Springer Verlag: Berlin.
Sugawara, T. and Lesser, V. 1993.On-line learning of coordination plans. COINS Technical Report 93-27, University of Massachussetts Computer Science Department.
Sugawara, T. and Lesser, V. 1995. Learning coordination plans in distributed OS environments. In Proceedings of the First International Conference on Multi-Agent Systems, V. Lesser (Ed.), San Francisco, CA, MIT Press, p. 462.
Sycara, K., Decker, K., Pannu, A., Williamson, M., and Zeng, D. 1996. Distributed intelligent agents. IEEE Expert, 11(6):36–46.
Tambe, M. 1995. Recursive agent and agent-group tracking in a realtime, dynamic environment. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 368–375.
Tambe, M. 1996. Tracking dynamic team activitys. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, Menlo Park, California, AAAI Press.
Tambe, M. 1997. Towards flexible teamwork. Journal of Artificial Intelligence Research, 7:81–124.
Tambe, M., Adibi, J., Al-Onaizan, Y., Erdem, A., Kaminka, A., Marsela, S.C., Muslea, I., and Tallis, M. 1998. Using an explicit model of teamwork in RoboCup-97. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 123–131.
Tan, M. 1993. Multi-agent reinforcement learning: Independent vs. cooperative agents. In Proceedings of the Tenth International Conference on Machine Learning, pp. 330–337.
Uchibe, E., Asada, M., and Hosoda, K. 1996. Behavior coordination for a mobile robot using modular reinforcement learning. In Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems 1996 (IROS' 96), pp. 1329–1336.
Uther, W.T.B. and Veloso, M.M. 1997. Generalizing adversarial reinforcement learning. In Proceedings of the AAAI Fall Symposium on Model Directed Autonomous Systems.
Veloso, M., Bowling, M., Achim, S., Han, K., and Stone, P. 1999. The CMUnited-98 champion small robot team. In RoboCup-98: Robot Soccer World Cup II, M. Asada and H. Kitano (Eds.), Springer Verlag: Berlin.
Veloso, M., Pagello, E., and Kitano, H. (Eds.). 2000. RoboCup-99: Robot Soccer World Cup III. Springer Verlag: Berlin.
Veloso, M., Stone, P., and Han, K. 1998a. CMUnited-97: RoboCup-97 small-robot world champion team. AI Magazine, 19(3):61–69.
Veloso, M., Stone, P., Han, K., and Achim, S. 1998b. The CMUnited-97 small-robot team. In RoboCup-97: Robot Soccer World Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 242–256.
Veloso, M. and Uther, W. 1999. The CMTrio-98 Sony legged robot team. In RoboCup-98: Robot Soccer World Cup II, M. Asada and H. Kitano (Eds.), Springer Verlag: Berlins.
Veloso, M., Uther, W., Fujita, M., Asada, M., and Kitano, H. 1998c. Playing soccer with legged robots. In Proceedings of IROS-98, Intelligent Robots and Systems Conferences, Victoria, Canada.
Vidal, J.M. and Durfee, E.H. 1995. Recursive agent modeling using limited rationality. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 376–383.
Walker, A. and Wooldridge, M. 1995. Understanding the emergence of conventions in multi-agent systems. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), Menlo Park, California, AAAI Press, pp. 384–389.
Wang, X. 1996. Planning while learning operators. In Proceedings of the Third International Conference on AI Planning Systems.
Weiß, G. 1995. Distributed reinforcement learning. Robotics and Autonomous Systems, 15:135–142.
Weiß, G. 1996. ECAI-96 Workshop on Learning in Distributed Arti-ficial Intelligence, Call for Papers.
Weiß, G. and Sen, S. (Eds.)(1996). Adaptation and Learning in Multiagent Systems, Springer Verlag: Berlin.
Yokota, K., Ozaki, K., Matsumoto, A., Kawabata, K., Kaetsu, H. and Asama, H. 1998. Omni-directional autonomous robots cooperating for team play. In RoboCup-97: Robot SoccerWorld Cup I, H. Kitano (Ed.), Springer Verlag: Berlin, pp. 333–347.
Zeng, D. and Sycara, K. 1998. Bayesian learning in negotiation. International Journal of Human-Computer Studies, 48:125–141.
Zlotkin, G. and Rosenschein, J.S. 1994. Coalition, cryptography, and stability: Mechanisms for coalition formation in task oriented domains. In Proceedings of the Twelfth National Conference on Artificial Intelligence, Menlo Park, California, AAAI Press, pp. 432–437.
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Stone, P., Veloso, M. Multiagent Systems: A Survey from a Machine Learning Perspective. Autonomous Robots 8, 345–383 (2000). https://doi.org/10.1023/A:1008942012299
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DOI: https://doi.org/10.1023/A:1008942012299