Predicting agents' behavior by measuring their social preferences

Kan Leung Cheng, Inon Zuckerman, Dana Nau, Jennifer Golbeck

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

2 Scopus citations


There are many situations in which two or more agents (e.g., human or computer decision makers) interact with each other repeatedly in settings that can be modeled as repeated stochastic games. In such situations, each agent's performance may depend greatly on how well it can predict the other agents' preferences and behavior. For use in making such predictions, we adapt and extend the Social Value Orientation (SVO) model from social psychology, which provides a way to measure an agent's preferences for both its own payoffs and those of the other agents. The original SVO model was limited to one-shot games, and assumed that each individual's behavioral preferences remain constant over time - an assumption that is inadequate for repeated-game settings, where an agent's future behavior may depend not only on its SVO but also on its observations of the other agents' behavior. We extend the SVO model to take this into account. Our experimental evaluation, on several dozen agents that were written by students in classroom projects, show that our extended model works quite well.

Original languageEnglish
Title of host publicationECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
EditorsTorsten Schaub, Gerhard Friedrich, Barry O'Sullivan
PublisherIOS Press BV
Number of pages2
ISBN (Electronic)9781614994183
StatePublished - 2014
Event21st European Conference on Artificial Intelligence, ECAI 2014 - Prague, Czech Republic
Duration: 18 Aug 201422 Aug 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


Conference21st European Conference on Artificial Intelligence, ECAI 2014
Country/TerritoryCzech Republic


Dive into the research topics of 'Predicting agents' behavior by measuring their social preferences'. Together they form a unique fingerprint.

Cite this