40 found
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  1. Syntactical Treatments of Propositional Attitudes.Michael Morreau & Sarit Kraus - 1998 - Artificial Intelligence 106 (1):161-177.
    Syntactical treatments of propositional attitudes are attractive to artificial intelligence researchers. But results of Montague (1974) and Thomason (1980) seem to show that syntactical treatments are not viable. They show that if representation languages are sufficiently expressive, then axiom schemes characterizing knowledge and belief give rise to paradox. Des Rivières and Levesque (1988) characterize a class of sentences within which these schemes can safely be instantiated. These sentences do not quantify over the propositional objects of knowledge and belief. We argue (...)
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  2. Utility-Based on-Line Exploration for Repeated Navigation in an Embedded Graph.Shlomo Argamon-Engelson, Sarit Kraus & Sigalit Sina - 1998 - Artificial Intelligence 101 (1-2):267-284.
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  3. Stable Repeated Strategies for Information Exchange Between Two Autonomous Agents.Rina Azoulay-Schwartz & Sarit Kraus - 2004 - Artificial Intelligence 154 (1-2):43-93.
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  4.  1
    Evaluating Practical Negotiating Agents: Results and Analysis of the 2011 International Competition.Tim Baarslag, Katsuhide Fujita, Enrico H. Gerding, Koen Hindriks, Takayuki Ito, Nicholas R. Jennings, Catholijn Jonker, Sarit Kraus, Raz Lin, Valentin Robu & Colin R. Williams - 2013 - Artificial Intelligence 198:73-103.
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  5. Making Friends on the Fly: Cooperating with New Teammates.Samuel Barrett, Avi Rosenfeld, Sarit Kraus & Peter Stone - 2017 - Artificial Intelligence 242:132-171.
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  6. Temporal Agent Programs.Jürgen Dix, Sarit Kraus & V. S. Subrahmanian - 2001 - Artificial Intelligence 127 (1):87-135.
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  7. Solving Coalitional Resource Games.Paul E. Dunne, Sarit Kraus, Efrat Manisterski & Michael Wooldridge - 2010 - Artificial Intelligence 174 (1):20-50.
  8. Nonmonotonicity and the Scope of Reasoning.David W. Etherington, Sarit Kraus & Donald Perlis - 1991 - Artificial Intelligence 52 (3):221-261.
  9. Agent Decision-Making in Open Mixed Networks.Ya'akov Gal, Barbara Grosz, Sarit Kraus, Avi Pfeffer & Stuart Shieber - 2010 - Artificial Intelligence 174 (18):1460-1480.
  10.  1
    A Logic-Based Model of Intention Formation and Action for Multi-Agent Subcontracting.John Grant, Sarit Kraus & Donald Perlis - 2005 - Artificial Intelligence 163 (2):163-201.
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  11.  21
    Manipulating Games by Sharing Information.John Grant, Sarit Kraus, Michael Wooldridge & Inon Zuckerman - 2014 - Studia Logica 102 (2):267-295.
    We address the issue of manipulating games through communication. In the specific setting we consider (a variation of Boolean games), we assume there is some set of environment variables, the values of which are not directly accessible to players; the players have their own beliefs about these variables, and make decisions about what actions to perform based on these beliefs. The communication we consider takes the form of (truthful) announcements about the values of some environment variables; the effect of an (...)
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  12.  75
    Postulates for Revising BDI Structures.John Grant, Sarit Kraus, Donald Perlis & Michael Wooldridge - 2010 - Synthese 175 (S1):39-62.
    The process of rationally revising beliefs in the light of new information is a topic of great importance and long-standing interest in artificial intelligence. Moreover, significant progress has been made in understanding the philosophical, logical, and computational foundations of belief revision. However, very little research has been reported with respect to the revision of other mental states, most notably propositional attitudes such as desires and intentions. In this paper, we present a first attempt to formulate a general framework for understanding (...)
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  13. Collaborative Plans for Complex Group Action.Barbara J. Grosz & Sarit Kraus - 1996 - Artificial Intelligence 86 (2):269-357.
  14. The Influence of Social Norms and Social Consciousness on Intention Reconciliation.Barbara J. Grosz, Sarit Kraus, David G. Sullivan & Sanmay Das - 2002 - Artificial Intelligence 142 (2):147-177.
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  15. Human–Computer Negotiation in a Three Player Market Setting.Galit Haim, Ya'akov Gal, Bo An & Sarit Kraus - 2017 - Artificial Intelligence 246:34-52.
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  16. On the Evaluation of Election Outcomes Under Uncertainty.Noam Hazon, Yonatan Aumann, Sarit Kraus & Michael Wooldridge - 2012 - Artificial Intelligence 189:1-18.
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  17. Physical Search Problems with Probabilistic Knowledge.Noam Hazon, Yonatan Aumann, Sarit Kraus & David Sarne - 2013 - Artificial Intelligence 196:26-52.
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  18. Diffusion Centrality: A Paradigm to Maximize Spread in Social Networks.Chanhyun Kang, Sarit Kraus, Cristian Molinaro, Francesca Spezzano & V. S. Subrahmanian - 2016 - Artificial Intelligence 239:70-96.
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  19. An Overview of Incentive Contracting.Sarit Kraus - 1996 - Artificial Intelligence 83 (2):297-346.
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  20. Multiagent Negotiation Under Time Constraints.Sarit Kraus, Jonathan Wilkenfeld & Gilad Zlotkin - 1995 - Artificial Intelligence 75 (2):297-345.
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  21. Multi-Agent Systems and Applications, Volume 2086 Of.Sarit Kraus - 2001 - In P. Bouquet (ed.), Lecture Notes in Artificial Intelligence. Kluwer Academic Publishers. pp. 150--172.
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  22. Negotiation and Cooperation in Multi-Agent Environments.Sarit Kraus - 1997 - Artificial Intelligence 94 (1-2):79-97.
  23. Nonmonotonic Reasoning, Preferential Models and Cumulative Logics.Sarit Kraus, Daniel Lehmann & Menachem Magidor - 1990 - Artificial Intelligence 44 (1-2):167-207.
  24. Reaching Agreements Through Argumentation: A Logical Model and Implementation.Sarit Kraus, Katia Sycara & Amir Evenchik - 1998 - Artificial Intelligence 104 (1-2):1-69.
  25. Resolving Crises Through Automated Bilateral Negotiations.Sarit Kraus, Penina Hoz-Weiss, Jonathan Wilkenfeld, David R. Andersen & Amy Pate - 2008 - Artificial Intelligence 172 (1):1-18.
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  26. Negotiating with Bounded Rational Agents in Environments with Incomplete Information Using an Automated Agent.Raz Lin, Sarit Kraus, Jonathan Wilkenfeld & James Barry - 2008 - Artificial Intelligence 172 (6-7):823-851.
  27. Robust Solutions to Stackelberg Games: Addressing Bounded Rationality and Limited Observations in Human Cognition.James Pita, Manish Jain, Milind Tambe, Fernando Ordóñez & Sarit Kraus - 2010 - Artificial Intelligence 174 (15):1142-1171.
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  28.  28
    Problems of Equivalence, Categoricity of Axioms and States Description in Databases.Tatjana L. Plotkin, Sarit Kraus & Boris I. Plotkin - 1998 - Studia Logica 61 (3):347-366.
    The paper is devoted to applications of algebraic logic to databases. In databases a query is represented by a formula of first order logic. The same query can be associated with different formulas. Thus, a query is a class of equivalent formulae: equivalence here being similar to that in the transition to the Lindenbaum-Tarski algebra. An algebra of queries is identified with the corresponding algebra of logic. An algebra of replies to the queries is also associated with algebraic logic. These (...)
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  29. A Study of Mechanisms for Improving Robotic Group Performance.Avi Rosenfeld, Gal A. Kaminka, Sarit Kraus & Onn Shehory - 2008 - Artificial Intelligence 172 (6-7):633-655.
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  30.  69
    Combining Psychological Models with Machine Learning to Better Predict People’s Decisions.Avi Rosenfeld, Inon Zuckerman, Amos Azaria & Sarit Kraus - 2012 - Synthese 189 (S1):81-93.
    Creating agents that proficiently interact with people is critical for many applications. Towards creating these agents, models are needed that effectively predict people's decisions in a variety of problems. To date, two approaches have been suggested to generally describe people's decision behavior. One approach creates a-priori predictions about people's behavior, either based on theoretical rational behavior or based on psychological models, including bounded rationality. A second type of approach focuses on creating models based exclusively on observations of people's behavior. At (...)
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  31.  1
    Intelligent Agent Supporting Human–Multi-Robot Team Collaboration.Ariel Rosenfeld, Noa Agmon, Oleg Maksimov & Sarit Kraus - 2017 - Artificial Intelligence 252:211-231.
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  32.  1
    When Security Games Hit Traffic: A Deployed Optimal Traffic Enforcement System.Ariel Rosenfeld, Oleg Maksimov & Sarit Kraus - 2020 - Artificial Intelligence 289:103381.
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  33. Managing Parallel Inquiries in Agents' Two-Sided Search.David Sarne & Sarit Kraus - 2008 - Artificial Intelligence 172 (4-5):541-569.
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  34. Emergent Cooperative Goal-Satisfaction in Large-Scale Automated-Agent Systems.Onn Shehory, Sarit Kraus & Osher Yadgar - 1999 - Artificial Intelligence 110 (1):1-55.
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  35. Methods for Task Allocation Via Agent Coalition Formation.Onn Shehory & Sarit Kraus - 1998 - Artificial Intelligence 101 (1-2):165-200.
  36. Forming K Coalitions and Facilitating Relationships in Social Networks.Liat Sless, Noam Hazon, Sarit Kraus & Michael Wooldridge - 2018 - Artificial Intelligence 259:217-245.
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  37.  1
    Multi-Robot Adversarial Patrolling: Handling Sequential Attacks.Efrat Sless Lin, Noa Agmon & Sarit Kraus - 2019 - Artificial Intelligence 274:1-25.
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  38. 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 203:35-65.
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  39. Incentive Engineering for Boolean Games.Michael Wooldridge, Ulle Endriss, Sarit Kraus & Jérôme Lang - 2013 - Artificial Intelligence 195:418-439.
  40. Computing the Fault Tolerance of Multi-Agent Deployment.Yingqian Zhang, Efrat Manisterski, Sarit Kraus, V. S. Subrahmanian & David Peleg - 2009 - Artificial Intelligence 173 (3-4):437-465.
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