ALA 2025

The goal of this workshop is to increase awareness of and interest in adaptive agent research, encourage collaboration and give a representative overview of current research in the area of adaptive and learning agents and multi-agent systems. It aims at bringing together not only scientists from different areas of computer science (e.g. agent architectures, reinforcement learning, evolutionary algorithms) but also from different fields studying similar concepts (e.g. game theory, bio-inspired control, mechanism design).

The workshop will serve as an inclusive forum for the discussion of ongoing or completed work covering both theoretical and practical aspects of adaptive and learning agents and multi-agent systems.

This workshop will focus on all aspects of adaptive and learning agents and multi-agent systems with a particular amphasis on how to modify established learning techniques and/or create new learning paradigms to address the many challenges presented by complex real-world problems. The topics of interest include but are not limited to:

• Novel combinations of reinforcement and supervised learning approaches
• Integrated learning approaches using reasoning modules like negotiation, trust, coordination, etc..
• Supervised and semi-supervised multi-agent learning
• Reinforcement learning (single- and multi-agent)
• Novel deep learning approaches for adaptive single- and multi-agent systems
• Multi-objective optimisation in single- and multi-agent systems
• Planning (single- and multi-agent)
• Reasoning (single- and multi-agent)
• Distributed learning
• Adaptation and learning in dynamic environments
• Evolution of agents in complex environments
• Co-evolution of agents in a multi-agent setting
• Cooperative exploration and learning to cooperate and collaborate
• Learning trust and reputation
• Communication restrictions and their impact on multi-agent coordination
• Design of reward structure and fitness measures for coordination
• Scaling learning techniques to large systems of learning and adaptive agents
• Emergent behaviour in adaptive multi-agent systems
• Game theoretical analysis of adaptive multi-agent systems
• Neuro-control in multi-agent systems
• Bio-inspired multi-agent systems
• Human-in-the-loop learning systems
• Applications of adaptive and learning agents and multi-agent systems to real world complex systems

Important Dates

• Submission Deadline: 4 February 2024 : 25 February 2024 1 March 2025 AOE
• Notification of acceptance: 10 March 2025 2 April 2025
• Camera-ready copies: 30 March 2025 1 May 2025
• Workshop: 19 - 20 May 2025

Submission Details

Papers can be submitted through OpenReview.

We invite submission of original work, up to 8 pages in length (excluding references) in the ACM proceedings format (i.e. following the AAMAS formatting instructions). This includes work that has been accepted as a poster/extended abstract at AAMAS 2025. Keeping with previous ALA guidelines, papers are limited to 8 pages plus references. Additionally, we welcome submission of preliminary results, i.e. work-in-progress, as well as visionary outlook papers that lay out directions for future research in a specific area, both up to 6 pages in length, although shorter papers are very much welcome, and will not be judged differently. Finally, we also accept recently published journal papers in the form of a 2 page abstract.

Furthermore, for submissions that were rejected or accepted as extended abstracts at AAMAS, authors need to also append the received reviews and a pdfdiff.

All submissions will be peer-reviewed (double-blind). Accepted work will be allocated time for poster and possibly oral presentation during the workshop. In line with AAMAS, the workshop will be fully offline.

When preparing your submission for ALA 2025, please be sure to remove the AAMAS copyright block, citation information and running headers. Please replace the AAMAS copyright block in the main.tex file from the AAMAS template with the following:

    \setcopyright{none}
    \acmConference[ALA '25]{Proc.\@ of the Adaptive and Learning Agents Workshop (ALA 2025)}{May 19 -- 20, 2025}{Detroit, Michigan, USA, ala-workshop.github.io}{Avalos, Aydeniz, M\"uller, Mohammedalamen (eds.)}
    \copyrightyear{2025}
    \acmYear{2025}
    \acmDOI{}
    \acmPrice{}
    \acmISBN{}
    \settopmatter{printacmref=false}
                            

For the submission of the camera-ready paper make sure to submit the deanonymized version with the replaced copyright block above.

Program

All times are presented in local Detroit time.

Monday May 19

Tuesday May 20

Poster Session A - Monday May 19 14:30-15:45

All papers presented on day 1.

Poster Session B - Tuesday May 20 14:30-15:45

All papers presented on day 2.

Accepted Papers

Invited Talks

Roxana Rădulescu

Affiliation: Utrecht University

Website: https://www.uu.nl/staff/RTRadulescu

Title: TBA

Bio: Roxana Rădulescu is Assistant Professor in AI and Data Science, at the Department of Information and Computing Sciences, at Utrecht University. Before, she was a FWO Postdoctoral fellow at the Artificial Intelligence Lab, Vrije Universiteit Brussel, Belgium. Her research is focussed on the development of multi-agent decision making systems where each agent is driven by different objectives and goals, under the paradigm of multi-objective multi-agent reinforcement learning.

Eugene Vinitsky

Affiliation: New York University

Website: https://engineering.nyu.edu/faculty/eugene-vinitsky

Title: TBA

Bio: Eugene Vinitsky is a Professor of Civil and Urban Engineering at NYU and a member of the C2SMARTER consortium. His primary research interest is figuring out how to make developing multi-agent controllers, planners, and intelligence as easy as possible by developing new learning algorithms, software, and tools. He looks for applications of these techniques in civil engineering problems and autonomy. He received his PhD in controls engineering from UC Berkeley.

Sandip Sen

Affiliation: University of Tulsa

Website: https://utulsa.edu/people/sandip-sen/

Title: TBA

Bio: Sandip Sen is a professor in the Tandy School of Computer Science with primary research interests in artificial intelligence, intelligent agents, machine learning, and evolutionary computation. He completed his Ph.D. on intelligent, distributed scheduling from the University of Michigan in December, 1993. He has authored approximately 300 papers in workshops, conferences, and journals in several areas of artificial intelligence.

Previous Editions

This workshop is a continuation of the long running AAMAS series of workshops on adaptive agents, now in its sixteenth year. Previous editions of this workshop may be found at the following urls:

• ALA-24
• ALA-23
• ALA-22
• ALA-21
• ALA-20
• ALA-19
• ALA-18
• ALA-17
• ALA-16
• ALA-15
• ALA-14
• ALA-13
• ALA-12
• ALA-11
• ALA-10
• ALA-09
• ALAMAS+ALAg-08
• ALAg-07
• Earlier editions

Programe Committee

• Erman Acar, University of Amsterdam<\li>
• Adrian Agogino, University of Texas, Austin<\li>
• Lucas N. Alegre, Institute of Informatics - Federal University of Rio Grande do Sul<\li>
• Nitay Alon, Hebrew University of Jerusalem<\li>
• Philipp Altmann, LMU Munich<\li>
• Hicham Azmani, Vrije Universiteit Brussel<\li>
• Jérôme Botoko Ekila, Vrije Universiteit Brussel<\li>
• Jacob Brue, University of Tulsa<\li>
• Mustafa Mert Çelikok, Delft University of Technology<\li>
• Fu-Chieh Chang, National Taiwan University<\li>
• Alexandra Cimpean, Vrije Universiteit Brussel<\li>
• Kyle Crandall, US Naval Research Lab<\li>
• Vinicius Renan de Carvalho, Universidade de São Paulo<\li>
• Gabriel de Oliveira Ramos, Universidade Vale do Rio dos Sinos<\li>
• Florent Delgrange, Vrije Universiteit Brussel<\li>
• Gaurav Dixit, Oregon State University<\li>
• Elias Fernández Domingos, Vrije Universiteit Brussel<\li>
• Simone Drago, Polytechnic Institute of Milan<\li>
• Flint Xiaofeng Fan, ETHZ - ETH Zurich<\li>
• Florian Felten, ETHZ - ETH Zurich<\li>
• Rolando Fernandez, University of Texas at Austin<\li>
• Timothy Flavin, University of Tulsa<\li>
• Julian Garcia, Monash University<\li>
• Everardo Gonzalez, Oregon State University<\li>
• Davide Grossi, University of Groningen<\li>
• Brent Harrison, University of Kentucky<\li>
• Fredrik Heintz, Linköping University<\li>
• Bernhard Hilpert, Leiden University<\li>
• Athirai Aravazhi Irissappane, Amazon<\li>
• Whiyoung Jung, LG AI Research<\li>
• Michael Kaisers, Google<\li>
• Thommen George Karimpanal, Deakin University<\li>
• Sammie Katt, Aalto University<\li>
• Guangliang Li, Ocean University of China<\li>
• Woohyung Lim, LG AI Research<\li>
• Robert Loftin, University of Sheffield<\li>
• Junlin Lu, National University of Ireland, Galway<\li>
• Joël Mathys, ETHZ - ETH Zurich<\li>
• David Milec, Czech Technical Univeresity in Prague, Czech Technical University of Prague<\li>
• Nicole Orzan, University of Groningen<\li>
• Bei Peng, University of Liverpool<\li>
• Ram Rachum, Tufts University<\li>
• Roxana Rădulescu, Utrecht University (ICS), Utrecht University<\li>
• Carrie Rebhuhn, The MITRE Corporation<\li>
• Mathieu Reymond, Mila - Quebec Artificial Intelligence Institute<\li>
• Juan Antonio Rodriguez Aguilar, Spanish National Research Council<\li>
• Manel Rodriguez-Soto, Artificial Intelligence Research Institute, Spanish National Research Council<\li>
• Diederik Roijers, University of Amsterdam<\li>
• Willem Röpke, Vrije Universiteit Brussel<\li>
• Andries Rosseau, Vrije Universiteit Brussel<\li>
• Vidyasagar Sadhu, SRI International<\li>
• Fernando P. Santos, University of Amsterdam<\li>
• Lukas Schäfer, Microsoft<\li>
• Sandip Sen, University of Tulsa<\li>
• Pedro Sequeira, SRI International<\li>
• William Tomlinson, University of California, Irvine<\li>
• Paolo Turrini, University of Warwick<\li>
• Pascal R. Van der Vaart, Delft University of Technology<\li>
• Garrett Warnell, University of Texas, Austin<\li>
• Connor Yates, Oregon State University<\li>
• Neil Yorke-Smith, Delft University of Technology<\li>

Organization

• Raphael Avalos (Vrije Universiteit Brussel, BE)
• A. Alp Aydeniz (Oregon State University, US)
• Henrik Müller (Leibniz University Hannover, DE)
• Montaser Mohammedalamen (University of Alberta, CA)

• Enda Howley (University of Galway, IE)
• Daniel Kudenko (Leibniz University Hannover, DE)
• Patrick Mannion (University of Galway, IE)
• Ann Nowé (Vrije Universiteit Brussel, BE)
• Sandip Sen (University of Tulsa, US)
• Peter Stone (University of Texas at Austin, US)
• Matthew Taylor (University of Alberta, CA)
• Kagan Tumer (Oregon State University, US)
• Karl Tuyls (University of Liverpool, UK)

Contact

If you have any questions about the ALA workshop, please contact the organizers at:
ala.workshop.aamas AT gmail.com

For more general news, discussion, collaboration and networking opportunities with others interested in Adaptive Learning Agents then please join our Linkedin Group

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