2016 IFAAMAS Award for Influential Papers in Autonomous Agents and Multiagent Systems
In 2006 The International Foundation for Autonomous Agents and Multi-Agent Systems established an award to recognize publications in the autonomous agents and multiagent systems field that have made influential and long-lasting contributions. 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 proven influential. A list of previous winners of this award is appended below.
This award is presented annually at the AAMAS Conference, in this case AAMAS-2016 in Singapore, in May. Winning papers must have been published at least 10 years before the award presentation. Therefore, papers eligible for the 2016 award must have been published in April 2005 or earlier, in a recognized forum (journal, conference, workshop).
To nominate a publication for this award, please send the full reference plus a brief statement (200 words or fewer) arguing the significance of the paper to Onn Shehory (chair of the 2016 committee for this award), email@example.com (Please put NOMINATION in the subject line.)
Nominations are due by the 8th of February 2016.
Previous Award Winners
MICHAEL L. LITTMAN (1994)
Markov games as a framework for multi-agent reinforcement learning.
Eleventh International Conference on Machine Learning (ICML-94), pp. 157-163, 1994.
ONN SHEHORY AND SARIT KRAUS (1998)
Methods for task allocation via agent coalition formation. Artificial
Intelligence, vol. 101 (1-2), May 1998, pp. 165-200
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,
MILIND TAMBE (1997)
Towards Flexible Teamwork", Journal of Artificial Intelligence
Research, 7, pp 83-124.
MICHAEL P. WELLMAN (1993)
A market-oriented programming environment and its application to
distributed multicommodity flow problems." Journal of Artificial
Intelligence Research, 1, pp. 1-23.
YOAV SHOHAM (1993)
Agent-oriented programming, Artificial Intelligence, 60, pp. 51-92.
YOKOO, M. DURFEE, E. H., ISHIDA, T. & KUWABARA, K. (1998)
The Distributed Constraint Satisfaction Problem: Formalization and
Algorithms. IEEE Transactions on Knowledge and Data Engineering
YOKOO, M. & HIRAYAMA, K. (1996)
Distributed Breakout Algorithm
for Solving Distributed Constraint Satisfaction Problems
Second International Conference on Multiagent Systems (ICMAS-96),
The award was given to the series of edited collections of papers on
Distributed AI published in the late 1980s:
HUHNS. M. H. (Ed.) (1987)
Distributed Artificial Intelligence. London, Pitman.
BOND, A. & GASSER, L. (Eds.) (1988)
Readings in Distributed Artificial Intelligence. San Mateo, CA, Morgan
GASSER L. & HUHNS, M. H. (Eds.) (1989)
Distributed Artificial Intelligence (Volume II). Pitman and Morgan
BRATMAN, M. E., ISRAEL, D. J. & POLLACK, M. E. (1988) Plans and
resource-bounded practical reasoning. Computational Intelligence, 4,
DURFEE, E. H. & LESSER, V. R. (1991) Partial global planning: A
coordination framework for distributed hypothesis formation. IEEE
Transactions on Systems, Man, and Cybernetics, 21, 1167-1183.
GROSZ, B. J. & KRAUS, S. (1996) Collaborative plans for complex group
action. Artificial Intelligence, 86, 269-357.
RAO, A. S. & GEORGEFF, M. P. (1991) Modeling rational agents within a
BDI-architecture. Second International Conference on Principles of
Knowledge Representation and Reasoning.
ROSENSCHEIN, J. S. & GENESERETH, M. R. (1985) Deals among rational
agents. Ninth International Joint Conference on Artificial
COHEN, P. R. & LEVESQUE, H. J. (1990) Intention is choice with
commitment. Artificial Intelligence, 42, 213-261.
DAVIS, R. & SMITH, R. G. (1983) Negotiation as a metaphor for
distributed problem solving. Artificial Intelligence, 20, 63-109.