Robust team decision-making under uncertainty
by Nalan Gulpinar, Ethem Canakoglu, Jo Thoms
International Journal of Applied Decision Sciences (IJADS), Vol. 3, No. 3, 2010

Abstract: This paper is concerned with multi-agent team modelling and robust decision-making problems arising in mission planning under uncertainty. We consider multi-agent planning problem with task coordination using stochastic programming. Agents within a centralised team cooperate so that the expected team performance is maximised. The success of each agent to accomplish any task is critical for the team performance. Inaccuracy on estimation of uncertain success probability is addressed using robust optimisation where different uncertainty sets are considered. Robust optimisation computes the optimal task allocation simultaneously with worst-case by taking into account of all scenarios. The computational results show trade-off between team efficiency and robustness of solution.

Online publication date: Tue, 19-Oct-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Applied Decision Sciences (IJADS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com