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Contextual and Possibilistic Reasoning for Coalition Formation

Bikakis, A; Caire, P; (2020) Contextual and Possibilistic Reasoning for Coalition Formation. AI , 1 (3) pp. 389-417. 10.3390/ai1030026. Green open access

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Abstract

In multi-agent systems, agents often need to cooperate and form coalitions to fulfil their goals, for example by carrying out certain actions together or by sharing their resources. In such situations, some questions that may arise are: Which agent(s) to cooperate with? What are the potential coalitions in which agents can achieve their goals? As the number of possibilities is potentially quite large, how to automate the process? And then, how to select the most appropriate coalition, taking into account the uncertainty in the agents’ abilities to carry out certain tasks? In this article, we address the question of how to identify and evaluate the potential agent coalitions, while taking into consideration the uncertainty around the agents’ actions. Our methodology is the following: We model multi-agent systems as Multi-Context Systems, by representing agents as contexts and the dependencies among agents as bridge rules. Using methods and tools for contextual reasoning, we compute all possible coalitions with which the agents can fulfil their goals. Finally, we evaluate the coalitions using appropriate metrics, each corresponding to a different requirement. To demonstrate our approach, we use an example from robotics.

Type: Article
Title: Contextual and Possibilistic Reasoning for Coalition Formation
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/ai1030026
Publisher version: https://doi.org/10.3390/ai1030026
Language: English
Additional information: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Keywords: multi-agent systems; coalition formation; Multi-Context Systems; contextual reasoning; possibilistic reasoning; reasoning under uncertainty
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > Dept of Information Studies
URI: https://discovery.ucl.ac.uk/id/eprint/10110626
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