ALA 2019

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

• 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

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 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 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
• Applications of adaptive and learning agents and multi-agent systems to real world complex systems

Extended and revised versions of papers presented at the workshop will be eligible for inclusion in a journal special issue (see below).

Important Dates

• Submission Deadline: 12 February 2019   extended to 5 March 2019 23:59 UTC
• Notification of acceptance: 10 March 2019   26 March 2019
• Camera-ready copies: 24 March 2019   9 April 2019
• Workshop: 13 - 14 May 2019

Submission Details

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 AAMAS 2019. 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 original papers presented at the workshop will also be eligible for inclusion in a post-proceedings journal special issue (journal to be confirmed).

Journal Special Issue

We are delighted to announce that extended versions of all original contributions at ALA 2019 will be eligible for inclusion in a special issue of The Knowledge Engineering Review (Impact Factor 1.07). The deadline for submitting extended papers will be 15 September 2019.

We will post further details about the submission process and expected publication timeline here after the workshop.

Program

Monday 13 May (Location: Room MB 9B)

Tuesday 14 May (Location: Room MB 9B)

Poster sessions

Poster session A - Monday 13 May 16:00 to 18:00

Papers presented in Sessions I - III together with:

• Jayakumar Subramanian, Raihan Seraj and Aditya Mahajan. Reinforcement Learning for Mean-field Teams
• Sanjeevan Ahilan and Peter Dayan. Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning
• Akshay Narayan and Tze-Yun Leong. Policy Transfer in Reinforcement Learning: A Selective Exploration Approach
• Han-Chao Wang, Tianpei Yang and Jianye Hao. Heuristically Adaptive Policy Reuse in Reinforcement Learning
• Yusuke Nakata and Sachiyo Arai. Bayesian Inverse Reinforcement Learning for Expert's Demonstrations in Multiple Dynamics
• Chad Peters, Babak Esfandiari, Amrik Sacha Elapata Gunaratne and Robert L. West. Behavioral Cloning in OpenAI using Case-Based Reasoning
• David Mguni. Using Stochastic Games for Learning to Control and Stop Optimally in Worst-Case Scenarios

Poster session B - Tuesday 14 May 16:00 to 18:00

Papers presented in Sessions IV - VI together with:

• Pierre-Edouard Osche, Sylvain Castagnos and Anne Boyer. From Music to Museum: Applications of Multi-Objective Ant Colony Systems to Real World Problems
• Theodore Perkins. Optimal Risk in Multiagent Blind Tournaments, with application to Yahtzee
• Adam Dees, James Hale and Sandip Sen. Evaluating Adaptive and Non-adaptive Strategies for Selecting and Orienting Influencer Agents for Effective Flock Control
• Zenefa Rahaman and Sandip Sen. Agent-based User-adapted Filters for Categories of Harassing Communication

Invited Talk

Garrett Warnell

Affiliation: Army Research Laboratory, The University of Texas at Austin (Visiting Researcher)

Website: http://www.cs.utexas.edu/users/ai-lab/?GarrettWarnell

Bio: Garrett Warnell is a research scientist with Army Research Laboratory's Computational and Information Sciences Directorate. He received BS degrees in mathematics and computer engineering from Michigan State University in 2009, and MS and PhD degrees in electrical engineering from The University of Maryland in 2013 and 2014, respectively. He joined Army Research Laboratory in 2014. In 2016, he became part of the ARL South extended campus community, and joined The University of Texas at Austin Department of Computer Science as a visiting researcher. His research interests are broadly in the areas of robotics, machine learning, and artificial intelligence, with current focuses on online and human-in-the-loop machine learning.

Talk Title: Human-in-the-Loop Machine Learning for Autonomy

Programe Committee

• Adrian Agogino, University of California, Santa Cruz, US
• Kiran Bangalore, AKKA, FR
• Feryal Behbahani, Latent Logic, UK
• Roland Bouffanais, Singapore University of Technology and Design, SG
• Jen Jen Chung, Eidgenössische Technische Hochschule Zürich, CH
• Felipe Leno da Silva, University of São Paulo, BR
• Sam Devlin, Microsoft Research, UK
• Yunshu Du, Washington State University, USA
• Kyriakos Efthymiadis, Vrije Universiteit Brussel, BE
• Elias Fernandez, Vrije Universiteit Brussel, BE
• Brent Harrison, Georgia Institute of Technology, USA
• Pablo Hernandez-Leal, Borealis AI, CA
• Mark Ho, Brown University, USA
• Richard Klima, University of Liverpool, UK
• Pieter Libin, Vrije Universiteit Brussel, BE
• Robert Loftin, North Carolina State University, USA
• Kleanthis Malialis, University of Cyprus, CY
• Karl Mason, Georgia Institute of Technology, US
• Kory Mathewson, University of Alberta, CA
• Felipe Meneguzzi, Pontifícia Universidade Católica do Rio Grande do Sul, BR
• Enrique Munoz de Cote, PROWLER.io, UK
• Hélène Plisnier, Vrije Universiteit Brussel, BE
• Gabriel Ramos, Vrije Universiteit Brussel, BE
• Carrie Rebhuhn, Oregon State University, USA
• Golden Rockefeller, Oregon State University, USA
• Diederik Roijers, Vrije Universiteit Amsterdam, NE
• Fernando Pedro Santos, Princeton University, USA
• Francisco Santos, Universidade de Lisboa, PT
• Aleksei Shpilman, JetBrains Research, RU
• Jivko Sinapov, Tufts University, USA
• Ibrahim Sobh, Valeo, EG
• Denis Steckelmacher, Vrije Universiteit Brussel, BE
• Peter Vamplew, Federation University Australia, AU
• Timothy Verstraeten, Vrije Universiteit Brussel, BE
• Connor Yates, Oregon State University, USA
• Luisa Zintgraf, University of Oxford, UK
• Shangtong Zhang, University of Oxford, UK

Organization

• Patrick MacAlpine (Microsoft Research, USA)
• Patrick Mannion (Galway-Mayo Institute of Technology, IE)
• Bei Peng (Microsoft Research, USA)
• Roxana Rădulescu (Vrije Universiteit Brussel, BE)

• Enda Howley (National University of Ireland Galway, IE)
• Daniel Kudenko (University of York, UK)
• Ann Nowé (Vrije Universiteit Brussel, BE)
• Sandip Sen (University of Tulsa, USA)
• Peter Stone (University of Texas at Austin, USA)
• Matthew Taylor (Washington State University, USA)
• Kagan Tumer (Oregon State University, USA)
• Karl Tuyls (University of Liverpool, UK)

Contact

If you have any questions about the ALA workshop, please contact the organizers at:
ala.workshop.2019 AT gmail.com

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