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Logical mechanism design

Published online by Cambridge University Press:  07 February 2011

Iyad Rahwan  and
Kate Larson
Iyad Rahwan*
Affiliation:
Computing & Information Science Program, Masdar Institute of Science & Technology, Abu Dhabi, UAE The Media Lab, Massachusetts Institute of Technology, Cambridge, 02139 MA, USA; e-mail: irahwan@acm.org
Kate Larson*
Affiliation:
Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, N2L 3G1, Canada; e-mail: klarson@cs.uwaterloo.ca
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Abstract

Game theory is becoming central to the design and analysis of computational mechanisms in which multiple entities interact strategically. The tools of mechanism design are used extensively to engineer incentives for truth revelation into resource allocation (e.g. combinatorial auctions) and preference aggregation protocols (e.g. voting). We argue that mechanism design can also be useful in the design of logical inference procedures. In particular, it can help us understand and engineer inference procedures when knowledge is distributed among self-interested agents. We set a research agenda for this emerging area, and point to some early research efforts.

Type
Articles
Information
The Knowledge Engineering Review , Volume 26 , Special Issue 1: 25th Anniversary Issue , 07 February 2011 , pp. 61 - 69
Copyright
Copyright © Cambridge University Press 2011

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References

Berners-Lee, T., Hendler, J., Lassila, O. 2001. The semantic web. Scientific American 29–37.Google ScholarPubMed
Chopra, S., Ghose, A., Meyer, T. 2006. Social choice theory, belief merging, and strategy-proofness. Information Fusion 7, 61–79.CrossRefGoogle Scholar
Conitzer, V., Sandholm, T., Lang, J. 2007. When are elections with few candidates hard to manipulate? Journal of the ACM 54(3), 14.CrossRefGoogle Scholar
Dung, P. M. 1995. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–358.CrossRefGoogle Scholar
Everaere, P., Konieczny, S., Marquis, P. 2007. The strategy-proofness landscape of merging. Journal of Artificial Intelligence Research 28, 49–105.CrossRefGoogle Scholar
Gabbay, D. M. 1995. What is a logical system?. In What is a Logical System? Gabbay, D. M. (ed.). Clarendon Press, 179–216.Google Scholar
Glazer, J., Rubinstein, A. 2001. Debates and decisions: on a rationale of argumentation rules. Games and Economic Behavior 36, 158–173.CrossRefGoogle Scholar
List, C., Puppe, C. 2009. Judgment aggregation: a survey. In The Oxford Handbook of Rational and Social Choice, Anand, P., Pattanaik, P. & Puppe, C. (eds). Oxford University Press.Google Scholar
Lorenzen, P. 1961. Ein dialogisches konstruktivitätskriterium. In Infinitistic Methods. Pergamon Press, 193–200.Google Scholar
Nisan, N., Roughgarden, T., Tardos, E., Vazirani, V. V. (eds). 2007. Algorithmic Game Theory. Cambridge University Press.CrossRefGoogle Scholar
Prakken, H., Sartor, G. 1997. Argument-based logic programming with defeasible priorities. Journal of Applied Non-classical Logics 7, 25–75.CrossRefGoogle Scholar
Rahwan, I., Larson, K. 2008. Mechanism design for abstract argumentation, In 7th International Joint Conference on Autonomous Agents & Multi Agent Systems, AAMAS'2008, Padgham, L., Parkes, D., Mueller, J. & Parsons, S. (eds). Estoril, Portugal, 1031–1038.Google Scholar
Rahwan, I., Tohmé, F. 2010. Collective argument evaluation as judgement aggregation. In 9th International Joint Conference on Autonomous Agents & Multi Agent Systems, AAMAS'2010, Toronto, Canada.Google Scholar
Rahwan, I., Larson, K., Tohmé, F. 2009. A characterisation of strategy-proofness for grounded argumentation semantics In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI), Pasadena CA, USA, 251–256.Google Scholar
Shoham, Y., Leyton-Brown, K. 2008. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. Cambridge University Press.CrossRefGoogle Scholar