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.
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 language | English |
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Title of host publication | Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020 |
Editors | Bo An, Amal El Fallah Seghrouchni, Gita Sukthankar |
Publisher | IFAAMAS |
Pages | 2209-2210 |
Number of pages | 2 |
ISBN (Electronic) | 978-1-4503-7518-4 |
Publication status | Published - May 2020 |
Event | The 19th International Conference on Autonomous Agents and Multi-Agent Systems - Auckland, New Zealand Duration: 9 May 2020 → 13 May 2020 Conference number: 19 https://aamas2020.conference.auckland.ac.nz/ https://aamas2020.conference.auckland.ac.nz |
Publication series
Name | Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS |
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Volume | 2020-May |
ISSN (Print) | 1548-8403 |
ISSN (Electronic) | 1558-2914 |
Conference
Conference | The 19th International Conference on Autonomous Agents and Multi-Agent Systems |
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Abbreviated title | AAMAS 2020 |
Country/Territory | New Zealand |
City | Auckland |
Period | 9/05/20 → 13/05/20 |
Internet address |