Threshold task games: Theory, platform and experiments

Kobi Gal, Ta Duy Nguyen, Quang Nhat Tran, Yair Zick

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

Abstract

Threshold task games (TTGs) are a class of cooperative games in which participants form coalitions to complete tasks associated with different rewards and thresholds for success. We provide efficient algorithms for computing approximately optimal coalition structures in TTGs. We also present non-trivial bounds on the cost of stability for this class. We put our theoretical results to practice; we design a web-based framework which allows human players to interact in a collaborative task-based model. Our analysis of human play in two different countries shows that players succeed in general to form optimal coalition structures, and converge to approximately stable payoff divisions.

Original languageAmerican English
Title of host publicationProceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
EditorsBo An, Amal El Fallah Seghrouchni, Gita Sukthankar
Pages393-401
Number of pages9
ISBN (Electronic)9781450375184
StatePublished - 1 Jan 2020
Event19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020 - Virtual, Auckland, New Zealand
Duration: 19 May 2020 → …

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2020-May

Conference

Conference19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2020
Country/TerritoryNew Zealand
CityVirtual, Auckland
Period19/05/20 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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