Incentive engineering for Boolean games

Ulle Endriss, Sarit Kraus, Jérôme Lang, Michael Wooldridge

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

We investigate the problem of influencing the preferences of players within a Boolean game so that, if all players act rationally, certain desirable outcomes will result. The way in which we influence preferences is by overlaying games with taxation schemes. In a Boolean game, each player has unique control of a set of Boolean variables, and the choices available to the player correspond to the possible assignments that may be made to these variables. Each player also has a goal, represented by a Boolean formula, that they desire to see satisfied. Whether or not a player's goal is satisfied will depend both on their own choices and on the choices of others, which gives Boolean games their strategic character. We extend this basic framework by introducing an external principal who is able to levy a taxation scheme on the game, which imposes a cost on every possible action that a player can choose. By designing a taxation scheme appropriately, it is possible to perturb the preferences of the players, so that they are incentivised to choose some equilibrium that would not otherwise be chosen. After motivating and formally presenting our model, we explore some issues surrounding it, including the complexity of finding a taxation scheme that implements some socially desirable outcome, and then discuss desirable properties of taxation schemes.

Original languageEnglish
Title of host publicationIJCAI 2011 - 22nd International Joint Conference on Artificial Intelligence
Pages2602-2607
Number of pages6
DOIs
StatePublished - 2011
Event22nd International Joint Conference on Artificial Intelligence, IJCAI 2011 - Barcelona, Catalonia, Spain
Duration: 16 Jul 201122 Jul 2011

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference22nd International Joint Conference on Artificial Intelligence, IJCAI 2011
Country/TerritorySpain
CityBarcelona, Catalonia
Period16/07/1122/07/11

Bibliographical note

Funding Information:
This paper has evolved from a paper that was published at the AAMAS-2011 conference [9]; a shorter version of the AAMAS-2011 paper was also published in the “best paper track” at the IJCAI-2011 conference. We thank the anonymous AAMAS and IJCAI referees for their useful and insightful comments. Lang thanks the project ComSoc (ANR-09-BLAN-0305-01). Wooldridge gratefully acknowledges the support of the European Research Council under Advanced Grant 291528 (“RACE”).

Funding

This paper has evolved from a paper that was published at the AAMAS-2011 conference [9]; a shorter version of the AAMAS-2011 paper was also published in the “best paper track” at the IJCAI-2011 conference. We thank the anonymous AAMAS and IJCAI referees for their useful and insightful comments. Lang thanks the project ComSoc (ANR-09-BLAN-0305-01). Wooldridge gratefully acknowledges the support of the European Research Council under Advanced Grant 291528 (“RACE”).

FundersFunder number
European Research Council291528

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