A Utility-Based Perspective on Multi-Objective Multi-Agent Decision Making: Doctoral Consortium

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Abstract

Numerous real-world problems involve multiple interacting entities and are inherently multi-objective in nature. Multi-objective multi-agent systems are a suitable paradigm to model such settings
Despite the rising interest in this field, it has become difficult to compare or categorise approaches and identify the state-of-the-art solutions. Therefore, our first contribution is to develop a new taxonomy on the basis of the reward structures and utility functions, to offer a more structured view of the field.
We note that utility functions are usually modelled as weights that define preferences over objectives, despite the fact that in many problems this assumption is not valid. We analyse the effect of non-linear utility functions on the set of equilibria in general multi-objective normal form games, under different optimisation criteria and look at how opponent modelling can aid the learning process in this setting.
For future work, we are interested in how sequential settings can be approached under these considerations, to get a step closer to creating hybrid, artificial-and-human, multi-agent collectives that can deal with the different preferences w.r.t. the objectives of the different agents in the collective.
Original languageEnglish
Title of host publicationProceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020
EditorsBo An, Amal El Fallah Seghrouchni, Gita Sukthankar
PublisherIFAAMAS
Pages2209-2210
Number of pages2
ISBN (Electronic)978-1-4503-7518-4
Publication statusPublished - May 2020
EventThe 19th International Conference on Autonomous Agents and Multi-Agent Systems - Auckland, New Zealand
Duration: 9 May 202013 May 2020
Conference number: 19
https://aamas2020.conference.auckland.ac.nz/
https://aamas2020.conference.auckland.ac.nz

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2020-May
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

ConferenceThe 19th International Conference on Autonomous Agents and Multi-Agent Systems
Abbreviated titleAAMAS 2020
Country/TerritoryNew Zealand
CityAuckland
Period9/05/2013/05/20
Internet address

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