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IFAAMAS Influential Paper Award

The Influential Paper Award seeks to recognize publications that have made influential and long-lasting contributions to the field. Candidates for this award are papers that have proved a key result, led to the development of a new subfield, demonstrated a significant new application or system, or simply presented a new way of thinking about a topic that has proved influential.

Previous winners of the award have been:
  • 2024:
    • Peyman Faratin, Carles Sierra, Nicholas R. Jennings (1998)
      Negotiation decision functions for autonomous agents
      Robotics and Autonomous Systems, Volume 24, Issues 3-4, pages 159-182
    • Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling (2000)
      Learning to cooperate via policy search
      Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence - AAAI-98, pages 746-752
  • 2023:
    • Caroline Claus, Craig Boutilier (1998)
      The dynamics of reinforcement learning in cooperative multiagent systems
      Proceedings of the Fifteenth National Conference on Artificial Intelligence - AAAI-98, pages 746-752
  • 2022:
    • Vince Conitzer, Tuomas Sandholm (2006)
      Computing the optimal strategy to commit to
      Proceedings of the 7th ACM Conference on Electronic Commerce - EC 06, pages 82-90
    • Jonathan Gratch, Stacy Marsella (2004)
      A domain-independent framework for modeling emotion
      Cognitive Systems Research, Volume 5, Issue 4, pages 269-306
  • 2021:
    • Rajeev Alur, Thomas A. Henzinger, Orna Kupferman (1997)
      Alternating-time Temporal Logic
      Proceedings of the 38th Annual Symposium on Foundations of Computer Science - FOCS '97, pages 100-109, and
      Journal of the ACM, Volume 49, Issue 5, September 2002, pages 672-713
    • Cynthia Breazeal (2003)
      Emotion and Sociable Humanoid Robots
      International Journal of Human-Computer Studies, Volume 59, Issues 1-2, pages 119-155
  • 2020:
    • A. Procaccia and M. Tennenholtz (2009)
      Approximate mechanism design without money
      Proceedings of the 10th ACM Conference on Electronic Commerce (ACM EC 2009), pages 177-186
    • K. Dresner and P. Stone (2008)
      A multiagent approach to autonomous intersection management
      Journal of Artificial Intelligence, Volume 31, pages 591-656.
  • 2019:
    • Bernstein, D. S., Zilberstein, S., & Immerman, N. (2000, June)
      The complexity of decentralized control of Markov decision processes
      Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, pages 32-37
    • Bernstein, D. S., Givan, R., Immerman, N., & Zilberstein, S. (2002)
      The complexity of decentralized control of Markov decision processes
      Mathematics of Operations Research, Volume 27, Issue 4, pages 819-840.
  • 2018:
    • Michael Wooldridge, Nicholas R. Jennings, and David Kinny (2000)
      The Gaia Methodology for Agent-Oriented Analysis and Design
      Journal of Autonomous Agents and Multi-Agent Systems, Volume 3, Issue 3, September 2000, pages 285-312
    • Franco Zambonelli, Nicholas R. Jennings, and Michael Wooldridge (2003)
      Developing Multiagent Systems: The Gaia Methodology
      ACM Transactions on Software Engineering Methodology, Volume 12, Issue 3, July 2003, pages 317-370
  • 2017:
    • Justine Cassell, Catherine Pelachaud, Norman Badler, Mark Steedman, Brett Achorn, Tripp Becket, Brett Douville, Scott Prevost, Matthew Stone (1994)
      Animated conversation: Rule-based generation of facial expression, gesture & spoken intonation for multiple conversational agents
      21st Annual Conference on Computer Graphics and Interactive Techniques, pages 413-420
    • W. Lewis Johnson, Jeff W. Rickel, James C. Lester (2000)
      Animated pedagogical agents: Face-to-face interaction in interactive learning environments
      International Journal of Artificial Intelligence in Education, Volume 11, pages 47-78
  • 2016:
    • Munindar P. Singh (1998)
      Agent Communication Languages: Rethinking the Principles
      IEEE Computer, Volume 31, No. 12, December 1998, pages 40-47
  • 2015:
    • Michael L. Littman (1994)
      Markov games as a framework for multi-agent reinforcement learning
      Proceedings of the Eleventh International Conference on Machine Learning (ICML-94), July 1994, pages 157-163
  • 2014:
    • Onn Shehory and Sarit Kraus (1998)
      Methods for task allocation via agent coalition formation
      Artificial Intelligence, Volume 101, Issues 1-2, May 1998, pages 165-200
  • 2013:
    • Cristiano Castelfranchi (1998)
      Modelling social action for AI agents
      Artificial Intelligence, Volume 103, Issues 1-2, August 1998, pages 157-182
    • Cristiano Castelfranchi (1995)
      Commitment: From individual intentions to groups and organizations
      First International Conference on Multi-Agent Systems, pages 41-49
  • 2012:
    • Michael P. Wellman (1993)
      A market-oriented programming enviornment and its application to distributed multicommodity flow problems
      Journal of Artificial Intelligence Research, Volume 1, pages 1-23 http://www.jair.org/papers/paper2.html
    • Milind Tambe (1997)
      Towards Flexible Teamwork
      Journal of Artificial Intelligence Research, Volume 7, pages 83-124 http://www.jair.org/papers/paper433.html
  • 2011:
    • Yoav Shoham (1993)
      Agent-oriented programming
      Artificial Intelligence, Volume 60, Issue 1, pages 51-92
  • 2010:
    • Makoto Yokoo, Edmund H. Durfee, Toru Ishida, and Kazuhiro Kuwabara (1998)
      The Distributed Constraint Satisfaction Problem: Formalization and Algorithms
      IEEE Transactions on Knowledge and Data Engineering 10:673-685
    • Makoto Yokoo and Katsutoshi Hirayama (1996)
      Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems
      Second International Conference on Multiagent Systems (ICMAS-96), pp.401-408
  • 2009:
    • M. N. Huhns. (Ed.) (1987)
      Distributed Artificial Intelligence. London, Pitman.
    • A. Bond and L. Gasser. (Eds.) (1988)
      Readings in Distributed Artificial Intelligence. San Mateo, CA, Morgan Kaufmann.
    • L. Gasser and M. N. Huhns. (Eds.) (1989)
      Distributed Artificial Intelligence (Volume II). Pitman and Morgan Kaufmann.
  • 2008:
    • M. E. Bratman, D. J. Israel and M. E. Pollack (1988)
      Plans and resource-bounded practical reasoning.
      Computational Intelligence, 4, pages 349-355.
    • E. H. Durfee and V. Lesser (1991)
      Partial global planning: A coordination framework for distributed hypothesis formation.
      In: IEEE Transactions on Systems, Man, and Cybernetics, 21, pages 1167-1183.
    • Special recognition given to:
      M. Wooldridge and N. R. Jennings (1995)
      Intelligent Agents: Theory and Practice
      The Knowledge Engineering Review, 10 (2), pp. 115-152.
  • 2007:
    • J. S. Rosenschein and M. R. Genesereth (1985)
      Deals Among Rational Agents.
      In: Proceedings of the 9th International Joint Conference on Artificial Intelligence, Los Angeles , California , August 1985, pages 91-99.
    • A. Rao and M. Georgeff (1991)
      Modelling rational agents within a BDI-architecture.
      In: Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning, Cambridge, Massachussets, pages 473-484.
    • B. J. Grosz and S. Kraus (1996)
      Collaborative Plans for Complex Group Actions.
      Artificial Intelligence, 86, pages 269-358.
  • 2006:
    • P. R. Cohen and H. Levesque (1990)
      Intention is choice with commitment.
      Artificial Intelligence , 42(2-3), pages 213-261.
    • R. Davis and R. Smith (1983)
      Negotiation as a Metaphor for Distributed Problem Solving.
      Artificial Intelligence, 20(1), pages 63-109.