A collaborative multiagent framework based on online risk-Aware planning and decision-making

Ivan Palomares, Ronan Killough, Kim Bauters, Weiru Liu, Jun Hong

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

5 Citations (Scopus)

Abstract

Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-Agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016
EditorsAnna Esposito, Miltos Alamaniotis, Amol Mali, Nikolaos Bourbakis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages25-32
Number of pages8
ISBN (Electronic)9781509044597
DOIs
Publication statusPublished - 2017 Jan 11
Event28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016 - San Jose, United States
Duration: 2016 Nov 62016 Nov 8

Publication series

NameProceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016

Conference

Conference28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016
Country/TerritoryUnited States
CitySan Jose
Period16-11-0616-11-08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

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