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On being a teammate: experiences acquired in the design of RoboCup teams

Authors:

Stacy Marsella,

Yaser Al-Onaizan,

Gal A. Kaminka,

Milind TambeAuthors Info & Claims

AGENTS '99: Proceedings of the third annual conference on Autonomous Agents

Pages 221 - 227

https://doi.org/10.1145/301136.301199

Published: 01 April 1999 Publication History

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References

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T. F. Bersano-Begey, P. O. Kenny, and E. H. Durfee. Agent teamwork, adaptive learning, and adversadal planning in robocup using a prs architecture. In RoboCup-97: The first robot world cup soccer games and conferences. Springer- Verlag, Heidelberg, Germany, 1998.]]

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S. Ch'ng and L. Padgham. Team description: Royal merlbourne knights. In RoboCup-97: The first robot world cup soccer games and conferences. Springer-Verlag, Heidelberg, Germany, 1998.]]

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H. Kitano, M. Asada, Y. Kuniyoshi, I. Nods, and g. Osawa. Robocup: The robot world cup initiative. In Proceedings of the first international conference on autonomous agents, 1997.]]

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H. Kitano, M. Tambe, P. Stone, S. Coradesci, H. Matsubara, M. Veloso, i. Nods, E. Osawa, and M. Asada. The robocup synthetic agents' challenge. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), August 1997.]]

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S. Luke, Hohn C, J. Farris, G. Jackson, and J. Hendler. Co-evolving soccer softbot team coordination with genetic programming. In RoboCup-97: The first robot world cup soccer games and conferences. Springer-Verlag, Heidelberg, Germany, 1998.]]

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P. Stone and M. Veloso. Task decomposition and dynamic role assignment for real-time strategic teamwork. In Proceedings of the international workshop on Agent theories, Architectures and Languages, 1998.]]

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P. Stone and M. Veloso. Using decision tree confidence factors for multiagent control. In RoboCup-97: The first robot world cup soccer games and conferences. Springer-Verlag, Heidelberg, Germany, 1998.]]

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R.S. Sutton. Learning to predict by the methods of temporal differences. Machine Learning, 3:9-44, 1988.]]

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M. Tambe. Towards flexible teamwork. Journal of Artificial Intelligence Research (JAIR), 7:83-124, 1997.]]

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M. Tambe, W. L. Johnson, R. Jones, F. Koss, J. E. Laird, P. S. Rosenbloom, and K. Schwamb. Intelligent agents for interactive simulation environments. AI Magazine, 16(1), Spring 1995.]]

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M. Wiiliamson, K. Sycara, and K. Decker. Executing decision-theoretic plans in multi-agent environments. In Proceedings of the AAAI Fall Symposium on Plan Execution: Problems and Issues, November 1996.]]

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K. Yokota, K. Ozako, Matsumoto A., T. Fujii, Asama H., and I. Endo. Cooperation towards team play. In Robo Cup- 97: The first robot world cup soccer games and conferences. Springer-Verlag, Heidelberg, Germany, 1998.]]

Cited By

Alhaji BBeecken JEhlers RGertheiss JMerz FMüller JPrilla MRausch AReinhardt AReinhardt DRembe CRohweder NSchwindt CWestphal SZimmermann J(2020)Engineering Human–Machine Teams for Trusted CollaborationBig Data and Cognitive Computing10.3390/bdcc40400354:4(35)Online publication date: 23-Nov-2020
https://doi.org/10.3390/bdcc4040035
Gan XGuo HLi Z(2019)A New Multi-Agent Reinforcement Learning Method based on Evolving Dynamic Correlation MatrixIEEE Access10.1109/ACCESS.2019.2946848(1-1)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2946848
Rakshit PKonar ARakshit PKonar A(2018)Agents and Multi-agent CoordinationPrinciples in Noisy Optimization10.1007/978-981-10-8642-7_2(57-88)Online publication date: 20-Nov-2018
https://doi.org/10.1007/978-981-10-8642-7_2
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Index Terms

On being a teammate: experiences acquired in the design of RoboCup teams
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
  2. Modeling and simulation
    1. Model development and analysis
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Expert systems

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cover image ACM Conferences

AGENTS '99: Proceedings of the third annual conference on Autonomous Agents

April 1999

441 pages

ISBN:158113066X

DOI:10.1145/301136

Copyright © 1999 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 April 1999

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Cited By

Alhaji BBeecken JEhlers RGertheiss JMerz FMüller JPrilla MRausch AReinhardt AReinhardt DRembe CRohweder NSchwindt CWestphal SZimmermann J(2020)Engineering Human–Machine Teams for Trusted CollaborationBig Data and Cognitive Computing10.3390/bdcc40400354:4(35)Online publication date: 23-Nov-2020
https://doi.org/10.3390/bdcc4040035
Gan XGuo HLi Z(2019)A New Multi-Agent Reinforcement Learning Method based on Evolving Dynamic Correlation MatrixIEEE Access10.1109/ACCESS.2019.2946848(1-1)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2946848
Rakshit PKonar ARakshit PKonar A(2018)Agents and Multi-agent CoordinationPrinciples in Noisy Optimization10.1007/978-981-10-8642-7_2(57-88)Online publication date: 20-Nov-2018
https://doi.org/10.1007/978-981-10-8642-7_2
Parker LRus DSukhatme G(2016)Multiple Mobile Robot SystemsSpringer Handbook of Robotics10.1007/978-3-319-32552-1_53(1335-1384)Online publication date: 27-Jul-2016
https://doi.org/10.1007/978-3-319-32552-1_53
Brüggemann BBrunner MSchulz D(2013)Spatially constrained coordinated navigation for a multi-robot systemAd Hoc Networks10.1016/j.adhoc.2012.06.01111:7(1919-1930)Online publication date: Sep-2013
https://doi.org/10.1016/j.adhoc.2012.06.011
Wilson AFern ATadepalli PLuck MSen S(2010)Bayesian role discovery for multi-agent reinforcement learningProceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 110.5555/1838206.1838494(1587-1588)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.5555/1838206.1838494
Guo HMeng Y(2010)Distributed Reinforcement Learning for Coordinate Multi-Robot ForagingJournal of Intelligent and Robotic Systems10.1007/s10846-010-9429-460:3-4(531-551)Online publication date: 1-Dec-2010
https://dl.acm.org/doi/10.1007/s10846-010-9429-4
Nguyen TKolp MPenserini L(2009)A development framework for component-based agent-oriented business servicesInternational Journal of Agent-Oriented Software Engineering10.1504/IJAOSE.2009.0236423:2/3(328-367)Online publication date: 1-Mar-2009
https://dl.acm.org/doi/10.1504/IJAOSE.2009.023642
Plant WSchaefer G(2009)An overview of neural networks in simulation soccer2009 World Congress on Nature & Biologically Inspired Computing (NaBIC)10.1109/NABIC.2009.5393661(1620-1625)Online publication date: Dec-2009
https://doi.org/10.1109/NABIC.2009.5393661
Plant WSchaefer GNakashima T(2008)An overview of Genetic Algorithms in simulation soccer2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)10.1109/CEC.2008.4631327(3897-3904)Online publication date: Jun-2008
https://doi.org/10.1109/CEC.2008.4631327
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