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ALA 2021 : Adaptive and Learning Agents @ AAMAS 2021


Conference Series : Adaptive and Learning Agents
When May 3, 2021 - May 4, 2021
Where London, UK
Submission Deadline Feb 10, 2021
Notification Due Mar 10, 2021
Final Version Due Mar 24, 2021
Categories    multi-agent systems   reinforcement learning   machine learning   artificial intelligence

Call For Papers

1st CfP: Adaptive and Learning Agents Workshop at AAMAS 2021 (London, UK)

Adaptive and Learning Agents Workshop at AAMAS (London, UK)

Submission deadline: February 10, 2021

Extended versions of all original contributions at ALA 2021 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 4.774).
* Workshop with a long and successful history, now in its thirteenth edition.
* Covering all aspects of adaptive and learning agents and multi-agent systems research.
* Open to original research papers, work-in-progress, and visionary outlook papers, as well as presentations on recently published journal papers.
* ACM proceedings (AAMAS) format up to 8 pages (excluding references) for original research, up to 6 pages for work-in-progress and outlook papers (shorter papers are also welcome and will not be judged differently) and 2 pages for recently published journal papers.
* Accepted papers are eligible for inclusion in a post-proceedings journal special issue.
* Submissions through easychair:


* Submission Deadline: February 10, 2021
* Notification of acceptance: March 10, 2021
* Camera-ready copies: March 24, 2021
* Workshop: May 3 & 4, 2020
* Extended submission deadline: September 15, 2021

Adaptive and learning agents, particularly those interacting with each other in a multi-agent setting, are becoming increasingly prominent as the size and complexity of real-world systems grows. How to adaptively control, coordinate and optimize such systems is an emerging multi-disciplinary research area at the intersection of Computer Science, Control Theory, Economics, and Biology. The ALA workshop will focus on agents and multi-agent systems which employ learning or adaptation.

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 but also from different fields studying similar concepts (e.g., game theory, bio-inspired control, mechanism design).

This workshop will focus on all aspects of adaptive and learning agents and multi-agent systems with a particular emphasis 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 in multi-agent systems
* Novel deep learning approaches for adaptive single and multi-agents systems
* Human-in-the-loop learning systems
* Planning and Reasoning (single and multi-agent)
* Distributed learning
* Adaptation and learning in dynamic environments
* Evolution and Co-evolution of agents in complex multi-agent environments
* Cooperative exploration
* 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 agents
* Emergent behavior in adaptive multi-agent systems
* Game theoretical analysis of adaptive multi-agent systems
* Neuro-control for adaptation in multi-agent systems
* Bio-inspired multi-agent systems
* Adaptive and learning agents for multi-objective decision making
* Multiple objectives in (multi-)agent systems
* Applications of adaptive agents, learning agents, and multi-agent systems to real world complex systems

In addition to these topics, this year we are particularly interested in exploring negative results that can serve as guidelines for early-stage researchers in the field of adaptive and learning single/multi-agent systems.


Papers can be submitted through EasyChair:

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 the AAMAS 2021 conference. 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.

All submissions will be peer-reviewed (single-blind). Accepted work will be allocated time for poster and possibly oral presentation during the workshop. Extended versions of all original contributions at ALA 2021 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 4.774). Deadline for submitting extended papers: September 15, 2021.

We look forward to receiving your submissions,

- The Organizers
Conor F. Hayes (NUI Galway, IE)
Roxana Rădulescu (Vrije Universiteit Brussel, BE)
Diederik M. Roijers (Vrije Universiteit Brussel, BE & HU University of Applied Sciences Utrecht, NL)
Fernando P. Santos (Princeton University, USA)
Felipe Leno da Silva (University of São Paulo, BR)


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