@inproceedings{fa3d1e28bbc04629b35640e3da7c7723,
title = "Utility-Based Sequential Decision-Making In Evidential Cooperative Multi-Agent Systems",
abstract = "This paper presents a new approach to building utili\&-based models of decision-makingin time-constrainedsituations with limited resources. A particular hierarchical homogenousmulti-agentarchitecture has been considered. Theproposed system combines agents{\textquoteright} belieji within the frame work of evidence theory and afler each observation maps the current set of cumulativepignistic probabilities into one of two actions: “defer decision” or “decide hypothesis i ”. The system maximizes the expected utility of delayed decisions minus cost. Theprocess of system adaptation to the environment is guided by reinforcement learning. The utilities-from-experts problem is simplified by learning utilities directly from feedbackon the qualiyof the decisions. The results of a case study are presented.",
keywords = "Decision utility, Distributed systems, Evidence theory, Multi-agent systems, Reinforcement learning, Sequential decision-making",
author = "Galina Rogova and Carlos Lollett and Peter Scott",
note = "Publisher Copyright: {\textcopyright} 2003 ISIF.; 6th International Conference on Information Fusion, FUSION 2003 ; Conference date: 08-07-2003 Through 11-07-2003",
year = "2003",
doi = "10.1109/icif.2003.177324",
language = "English",
isbn = "0972184449",
series = "Proceedings of the 6th International Conference on Information Fusion, FUSION 2003",
publisher = "IEEE Computer Society",
pages = "823--830",
booktitle = "Proceedings of the 6th International Conference on Information Fusion, FUSION 2003",
address = "United States",
}