TY - GEN
T1 - A collaborative multiagent framework based on online risk-Aware planning and decision-making
AU - Palomares, Ivan
AU - Killough, Ronan
AU - Bauters, Kim
AU - Liu, Weiru
AU - Hong, Jun
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/11
Y1 - 2017/1/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85013647047&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85013647047&partnerID=8YFLogxK
U2 - 10.1109/ICTAI.2016.12
DO - 10.1109/ICTAI.2016.12
M3 - Conference contribution
AN - SCOPUS:85013647047
T3 - Proceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016
SP - 25
EP - 32
BT - Proceedings - 2016 IEEE 28th International Conference on Tools with Artificial Intelligence, ICTAI 2016
A2 - Esposito, Anna
A2 - Alamaniotis, Miltos
A2 - Mali, Amol
A2 - Bourbakis, Nikolaos
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2016
Y2 - 6 November 2016 through 8 November 2016
ER -