13 found
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  1.  13
    Computing cooperative solution concepts in coalitional skill games.Yoram Bachrach, David C. Parkes & Jeffrey S. Rosenschein - 2013 - Artificial Intelligence 204 (C):1-21.
  2.  24
    Strategyproof peer selection using randomization, partitioning, and apportionment.Haris Aziz, Omer Lev, Nicholas Mattei, Jeffrey S. Rosenschein & Toby Walsh - 2019 - Artificial Intelligence 275 (C):295-309.
  3.  11
    The learnability of voting rules.Ariel D. Procaccia, Aviv Zohar, Yoni Peleg & Jeffrey S. Rosenschein - 2009 - Artificial Intelligence 173 (12-13):1133-1149.
  4.  8
    Mechanism design for automated negotiation, and its application to task oriented domains.Gilad Zlotkin & Jeffrey S. Rosenschein - 1996 - Artificial Intelligence 86 (2):195-244.
  5.  12
    Algorithms for the coalitional manipulation problem.Michael Zuckerman, Ariel D. Procaccia & Jeffrey S. Rosenschein - 2009 - Artificial Intelligence 173 (2):392-412.
  6.  13
    On the approximability of Dodgson and Young elections.Ioannis Caragiannis, Jason A. Covey, Michal Feldman, Christopher M. Homan, Christos Kaklamanis, Nikos Karanikolas, Ariel D. Procaccia & Jeffrey S. Rosenschein - 2012 - Artificial Intelligence 187-188 (C):31-51.
  7.  8
    Iterative voting and acyclic games.Reshef Meir, Maria Polukarov, Jeffrey S. Rosenschein & Nicholas R. Jennings - 2017 - Artificial Intelligence 252 (C):100-122.
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  8.  13
    Mechanisms for information elicitation.Aviv Zohar & Jeffrey S. Rosenschein - 2008 - Artificial Intelligence 172 (16-17):1917-1939.
  9.  12
    Deriving consensus in multiagent systems.Eithan Ephrati & Jeffrey S. Rosenschein - 1996 - Artificial Intelligence 87 (1-2):21-74.
  10.  10
    Compromise in negotiation: exploiting worth functions over states.Gilad Zlotkin & Jeffrey S. Rosenschein - 1996 - Artificial Intelligence 84 (1-2):151-176.
  11.  21
    Effort Games and the Price of Myopia.Yoram Bachrach, Michael Zuckerman & Jeffrey S. Rosenschein - 2009 - Mathematical Logic Quarterly 55 (4):377-396.
    We consider Effort Games, a game-theoretic model of cooperation in open environments, which is a variant of the principal-agent problem from economic theory. In our multiagent domain, a common project depends on various tasks; carrying out certain subsets of the tasks completes the project successfully, while carrying out other subsets does not. The probability of carrying out a task is higher when the agent in charge of it exerts effort, at a certain cost for that agent. A central authority, called (...)
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  12.  14
    Algorithms for strategyproof classification.Reshef Meir, Ariel D. Procaccia & Jeffrey S. Rosenschein - 2012 - Artificial Intelligence 186 (C):123-156.
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  13.  11
    Teaching and leading an ad hoc teammate: Collaboration without pre-coordination.Peter Stone, Gal A. Kaminka, Sarit Kraus, Jeffrey S. Rosenschein & Noa Agmon - 2013 - Artificial Intelligence 203 (C):35-65.
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