A quantitative analysis of decision process in social groups using human trajectories

Truc Viet Le, Siyuan Liu, Hoong Chuin Lau, Ramayya Krishnan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

A group's collective action is an outcome of the group's decision-making process, which may be reached by either averaging of the individual preferences or following the choices of certain members in the group. Our problem here is to decide which decision process the group has adopted given the data of the collective actions. We propose a generic statistical framework to infer the group's decision process from the spatio-temporal data of group trajectories, where each "trajectory" is a sequence of group actions. This is achieved by systematically comparing each agent type's influence on the group actions based on an array of spatio-temporal criteria. Results of those comparisons are then aggregated into a score to make inference about the group's decision process.

Original languageEnglish (US)
Title of host publication13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1425-1426
Number of pages2
Volume2
ISBN (Electronic)9781634391313
Publication statusPublished - Jan 1 2014
Event13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 - Paris, France
Duration: May 5 2014May 9 2014

Other

Other13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
CountryFrance
CityParis
Period5/5/145/9/14

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Le, T. V., Liu, S., Lau, H. C., & Krishnan, R. (2014). A quantitative analysis of decision process in social groups using human trajectories. In 13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 (Vol. 2, pp. 1425-1426). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).