In recent years there has been a growing awareness of the need for automated and assistive decision making systems to move beyond single-objective formulations when dealing with complex real-world issues, which invariably involve multiple competing objectives. The purpose of this special issue is to promote collaboration and cross-fertilisation of ideas between researchers working in different areas of multi-objective decision making and on the topics of interest below, and to provide a forum for dissemination of high-quality multi-objective decision making research.
The special issue targets high-quality original papers covering all aspects of multi-objective decision making, including, but not limited to, the list of topics below. Manuscripts that extend a previous conference or workshop publication are welcome, provided that there is a significant amount of new material in the submission (i.e. the manuscript should contain at least 50% new material).
Patrick Mannion, National University of Ireland Galway, Ireland
Diederik M. Roijers, HU University Of Applied Sciences Utrecht, Netherlands
Peter Vamplew, Federation University, Australia
Richard Dazeley, Deakin University, Australia
The following is a non-exhaustive list of topics that we would like to cover in the special issue:
- Multi-objective/multi-criteria/multi-attribute decision making
- Multi-objective reinforcement learning
- Multi-objective planning and scheduling
- Multi-objective multi-agent decision making
- Multi-objective game theory
- Multi-objective/multi-criteria/multi-attribute utility theory
- Preference elicitation for MODeM
- Social choice and MODeM
- Multi-objective decision support systems
- Multi-objective metaheuristic optimisation (e.g. evolutionary algorithms) for autonomous agents and multi-agent systems
- Explainable MODeM
- Applications of MODeM
Submission deadline: October 1, 2021
Manuscript submissions will be considered for publication in the MODeM special issue on a continuous basis until the submission deadline. Submissions accepted for publication before the completion of the special issue will be available on the journal website shortly after acceptance.
To submit, you should visit the online system at https://www.editorialmanager.com/agnt/ and create a new account if you do not already have one. When creating your submission on the system, select the submission type “Original Article”, and then in the “Additional Information” section, answer “Yes” when asked if your manuscript belongs to a special issue, then select “S.I. : Multi-Objective Decision Making”. If you do not mark your manuscript correctly as belonging to the MODeM special issue, it may not reach the correct editors.
Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals.
All papers will be reviewed following standard reviewing procedures for the Journal.
Papers must be prepared in accordance with the Journal guidelines: www.springer.com/10458
Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including FAQs, Tutorials along with Help and Support.
Other links include:
MODeM 2021 workshop
In support of this special issue, an online workshop on multi-objective decision making (MODeM 2021) will be held during July 2021 (details TBC). Authors considering submitting to the special issue may also consider submitting a preliminary version of their work to the MODeM 2021 workshop to facilitate opportunities for collaboration and cross-fertilisation of ideas between researchers working in different fields. Submission of preliminary work to the MODeM 2021 workshop does not confer an automatic entitlement to publish in the JAAMAS MODeM special issue; all special issue submissions must pass through the same rigorous JAAMAS review process and meet the standard JAAMAS publication criteria. The JAAMAS MODeM special issue has an open call for papers; it is not necessary to submit preliminary work to the MODeM 2021 workshop in order to have your manuscript considered for publication in this SI.
Patrick Mannion is a Lecturer in the School of Computer Science at National University of Ireland Galway, and also serves as Deputy Editor of The Knowledge Engineering Review journal. He is a former Irish Research Council Scholar, and a former Fulbright Scholar. Dr Mannion served as Co-Chair for the 2017, 2018 and 2019 editions of the Adaptive and Learning Agents workshop series. He is a co-author of the survey on multi-objective multi-agent decision making that was recently published in JAAMAS (https://doi.org/10.1007/s10458-019-09433-x). His main research interests include (sequential) decision making, multi-agent systems, multi-objective optimisation, game theory and metaheuristic algorithms.
Diederik M. Roijers is a Senior Lecturer in Technical Computer Science, and member of the Microsystems Technology research group at HU University Of Applied Sciences Utrecht in the Netherlands, and Senior Researcher at the AI research group at the Vrije Universiteit Brussel in Brussels, Belgium. He is a co-author of the survey on multi-objective multi-agent decision making that was recently published in JAAMAS (https://doi.org/10.1007/s10458-019-09433-x), and first author of the seminal survey on multi-objective decision making in JAIR (http://dx.doi.org/10.1613/jair.3987) as well as the book on this topic in the Synthesis Lectures on Artificial Intelligence and Machine Learning series from Morgan and Claypool (http://dx.doi.org/10.2200/S00765ED1V01Y201704AIM034). His main research interests are reinforcement learning, decision-theoretic planning and multi-agent systems, especially with multiple objectives.
Peter Vamplew is an Associate Professor in Information Technology within the school of Science, Engineering and Information Technology at Federation University. He is currently an Associate editor for Neurocomputing journal. He has been a pioneer in multi-objective reinforcement learning research for over a decade, including co-authoring a key survey of multi-objective sequential decision-making (http://dx.doi.org/10.1613/jair.3987). His main interests are the development, evaluation and application of multi-objective reinforcement learning algorithms, particularly in the context of developing safe and ethical autonomous agents.
Richard Dazeley is an Associate Professor of Computer Science at Deakin University (Geelong) where he is the Deputy Leader of the Machine Intelligence Lab and Director of the Master of Applied Artificial Intelligence. Along with over a dozen papers in multi-objective reinforcement learning and optimisation he is also the co-author of the seminal survey on multi-objective decision making in JAIR (http://dx.doi.org/10.1613/jair.3987). He was a member of the IEEE P7001 Transparency of Autonomous Systems working group and has organised and served on numerous program committees for many leading conferences such as ACKMIDS, AAMAS, PRICAI, IJCAI, ALA and regularly reviews for leading journals e.g. AIJ, Neurocomputing, TKDE, JRPIT and KAIS. His current research interests are in applying reinforcement learning and multi-objective principles in the development of interactive, safe, ethical and explainable systems.