A Brief Guide to Multi-Objective Reinforcement Learning and Planning: JAAMAS Track

Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowe, Gabriel De Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Real-world sequential decision-making tasks are usually complex, and require trade-offs between multiple -- often conflicting -- objectives. However, the majority of research in reinforcement learning (RL) and decision-theoretic planning assumes a single objective, or that multiple objectives can be handled via a predefined weighted sum over the objectives. Such approaches may oversimplify the underlying problem, and produce suboptimal results.
This extended abstract outlines the limitations of using a semi-blind iterative process to solve multi-objective decision making problems. Our extended paper serves as a guide for the application of explicitly multi-objective methods to difficult problems.
Original languageEnglish
Title of host publicationThe 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023)
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1988-1990
Number of pages3
Volume2023-May
ISBN (Electronic)978-1-4503-9432-1
Publication statusPublished - May 2023
EventThe 22nd International Conference on Autonomous Agents and Multiagent Systems - London, United Kingdom
Duration: 29 May 20232 Jun 2023
https://aamas2023.soton.ac.uk

Publication series

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

Conference

ConferenceThe 22nd International Conference on Autonomous Agents and Multiagent Systems
Abbreviated titleAAMAS 2023
Country/TerritoryUnited Kingdom
CityLondon
Period29/05/232/06/23
Internet address

Bibliographical note

Funding Information:
Conor F. Hayes is funded by the University of Galway Hardiman Scholarship. This research was supported by funding from the Flemish Government under the “Onderzoeksprogramma Artificiële Intelligentie (AI) Vlaanderen” program. Roxana Rădulescu is supported by the Research Foundation Flanders (FWO postdoctoral fellowship 1286223N). Johan Källström and Fredrik Heintz were partially supported by the Swedish Governmental Agency for Innovation Systems (grant NFFP7/2017-04885), and the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation. Luisa Zintgraf was supported by the 2017 Microsoft Research PhD Scholarship Program, and the 2020 Microsoft Research EMEA PhD Award.

Publisher Copyright:
© 2023 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

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