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

Palomares, Iv�n; Killough, Ronan; Bauters, Kim; Liu, Weiru; Hong, Jun

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 compre- hensive 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 modelling and multi- criteria 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.

• Journal Article Type: Article
• Conference Name: Tools with Artificial Intelligence (ICTAI), 2016 IEEE 28th International Conference on
• Acceptance Date: Nov 6, 2016
• Publication Date: Jan 16, 2017
• Deposit Date: Feb 17, 2017
• Publicly Available Date: Oct 3, 2017
• Journal: 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)
• Print ISSN: 2375-0197
• Peer Reviewed: Peer Reviewed
• Pages: 25-32
• Keywords: online risk-aware planning, collaborative multiagent framework, decision making
• Public URL: https://uwe-repository.worktribe.com/output/899987
• Publisher URL: http://dx.doi.org/10.1109/ICTAI.2016.0015
• Additional Information: Additional Information : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; Title of Conference or Conference Proceedings : Proceedings of the IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI 2016)
• Contract Date: Feb 17, 2017