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

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

研究成果: Conference contribution

5 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題Proceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016
編輯Anna Esposito, Miltos Alamaniotis, Amol Mali, Nikolaos Bourbakis
發行者Institute of Electrical and Electronics Engineers Inc.
頁面25-32
頁數8
ISBN(電子)9781509044597
DOIs
出版狀態Published - 2017 1月 11
事件28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016 - San Jose, United States
持續時間: 2016 11月 62016 11月 8

出版系列

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

Conference

Conference28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016
國家/地區United States
城市San Jose
期間16-11-0616-11-08

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用

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