Modeling social preferences in multi-player games

Brandon Wilson, Inon Zuckerman, Dana Nau

Research output: Contribution to conferencePaperpeer-review


Game-tree search algorithms have contributed greatly to the success of computerized players in two-player extensive-form games. In multi-player games there has been less success, partly because of the difficulty of recognizing and reasoning about the inter-player relationships that often develop and change during human game-play. Simplifying assumptions (e.g., assuming each player selfishly aims to maximize its own payoff) have not worked very well in practice. We describe a new algorithm for multi-player games, So- cially-oriented Search (SOS), that incorporates ideas from Social Value Orientation theory from social psychology. We provide a theoretical study of the algorithm, and a method for recognizing and reasoning about relationships as they develop and change during a game. Our empirical evaluations of SOS in the strategic board game Quoridor show it to be significantly more effective against players with dynamic interrelationships than the current state-of-the-art algorithms. Categories and Subject Descriptors 1.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search-Graph and tree search strategies General Terms Economics, Algorithms.

Original languageEnglish
Number of pages8
StatePublished - 2011
Externally publishedYes
Event10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 - Taipei, Taiwan, Province of China
Duration: 2 May 20116 May 2011


Conference10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011
Country/TerritoryTaiwan, Province of China


  • Game-tree search
  • Multi-player games

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence


Dive into the research topics of 'Modeling social preferences in multi-player games'. Together they form a unique fingerprint.

Cite this