Many real-world decision problems are inherently multi-objective in nature and concern multiple actors, making multi-objective multi- agent systems a key domain to study. We argue that trade-offs between conflicting objective functions should be analysed on the basis of the utility that these trade-offs have for the users of a system. We develop a new taxonomy which classifies multi-objective multi-agent decision making settings, on the basis of the reward structures and utility functions. We analyse which solution concepts apply to the different settings in our taxonomy, which allows us to offer a structured view of the field and identify promising directions for future research.
Original languageEnglish
Title of host publicationProceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020
PublisherIFAAMAS
Publication statusAccepted/In press - 1 Mar 2020
EventThe 19th International Conference on Autonomous Agents and Multi-Agent Systems 2020 - Auckland, New Zealand
Duration: 9 May 202013 May 2020
https://aamas2020.conference.auckland.ac.nz

Conference

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

ID: 49911076