Incentive engineering for Boolean games

Michael Wooldridge, Ulle Endriss, Sarit Kraus, Jér̂ome Lang

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

Boolean games are a natural, compact, and expressive class of logic-based games, in which each player exercises unique control over some set of Boolean variables, and has some logical goal formula that it desires to be achieved. A player's strategy set is the set of all possible valuations that may be made to its variables. A player's goal formula may contain variables controlled by other agents, and in this case, it must reason strategically about how best to assign values to its variables. In the present paper, we consider the possibility of overlaying Boolean games with taxation schemes. A taxation scheme imposes a cost on every possible assignment an agent can make. By designing a taxation scheme appropriately, it is possible to perturb the preferences of agents so that they are rationally incentivised to choose some desirable equilibrium that might not otherwise be chosen, or incentivised to rule out some undesirable equilibria. After formally presenting the model, we explore some issues surrounding it (e.g., the complexity of finding a taxation scheme that implements some desirable outcome), and then discuss possible desirable properties of taxation schemes.

Original languageEnglish
Pages (from-to)418-439
Number of pages22
JournalArtificial Intelligence
Volume195
DOIs
StatePublished - 2013

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”).

Keywords

  • Boolean games
  • Manipulation
  • Multi-agent systems
  • Taxation

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