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ALA 2020 : Adaptive and Learning Agents Workshop @ AAMAS 2020


Conference Series : Adaptive and Learning Agents
When May 9, 2020 - May 10, 2020
Where Auckland, New Zealand
Submission Deadline Feb 24, 2020
Notification Due Mar 10, 2020
Final Version Due Mar 24, 2020
Categories    artificial intelligence   machine learning   reinforcement learning   multi-agent systems

Call For Papers

Dear all,

We are organizing the next iteration of the Adaptive and Learning Agents (ALA) workshop at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS) in Auckland. Please find the CfP below.


Adaptive and Learning Agents Workshop at AAMAS (Auckland, New Zealand)

Extended submission deadline: February 24, 2020

Extended versions of all original contributions at ALA 2020 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 4.213).



* Workshop with a long and successful history, now in its eleventh 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 (extended): February 24, 2020

* Notification of acceptance: March 10, 2020

* Camera-ready copies: March 24, 2020

* Workshop: May 9 & 10, 2020



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 that work with other agent reasoning modules like negotiation, trust models, coordination, etc.

* 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 behavior in adaptive multi-agent systems

* Game theoretical analysis of adaptive multi-agent systems

* Neuro-control in multi-agent systems

* Bio-inspired multi-agent systems

* Adaptive and learning agents for multi-objective decision making

* Applications of adaptive and learning agents and multi-agent systems to real world complex 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 2020 conference (we encourage authors to append the received reviews and a short letter highlighting the changes carried out on the paper; the reviews can be appended at the end of the submission file and do not count towards the page limit). 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 2020 will be eligible for inclusion in a special issue of the Springer journal Neural Computing and Applications (Impact Factor 4.213).

We look forward to receiving your submissions,

- The Organizers

Patrick MacAlpine (Microsoft Research, USA)

Fernando P. Santos (Princeton University, USA)

Felipe Leno da Silva (University of São Paulo, BR)

Roxana Rădulescu (Vrije Universiteit Brussel, BE)


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