• 2 May 2019: The preliminary program is now online!
  • 29 April 2019: We are happy to announce our invited speaker for this year, Dr. Garrett Warnell.
  • 6 March 2019: Submissions are now closed. We received 36 submissions this year!
  • 26 February 2019: The submission deadline has been extended to 5 March 2019 23:59 UTC!
  • 5 February 2019: The submission deadline has been extended to 26 February 2019 23:59 UTC!
  • 4 February 2019: Program Committee members added
  • 6 December 2018: ALA 2019 site launched

ALA 2019 - Workshop at AAMAS 2019

Adaptive and Learning Agents (ALA) encompasses diverse fields such as Computer Science, Software Engineering, Biology, as well as Cognitive and Social Sciences. The ALA workshop will focus on agents and multiagent systems which employ learning or adaptation.

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:

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.


Monday 13 May (Location: Room MB 9B)

08:45 - 09:00 Welcome & Opening Remarks
09:00 - 10:30 Session I - Chair: Patrick Mannion
09:00 - 10:00 Invited Talk: Garrett Warnell
Human-in-the-Loop Machine Learning for Autonomy
10:00 - 10:30
Long Talk: Gabriel de La Cruz, Yunshu Du and Matthew E. Taylor
Jointly Pre-training with Supervised, Autoencoder, and Value Losses for Deep Reinforcement Learning
10:30 - 11:00 Coffee Break
11:00 - 12:30 Session II - Chair: Fernando P. Santos
11:00 - 11:30
Long Talk: Bilal Kartal, Pablo Hernandez-Leal, Chao Gao and Matthew E. Taylor
Safer Deep RL with Shallow MCTS: A Case Study in Pommerman
11:30 - 12:00
Long Talk: Felipe Leno Da Silva, Anna Helena Reali Costa and Peter Stone
Distributional Reinforcement Learning Applied to Robot Soccer Simulation
12:00 - 12:15 Short Talk: Miguel Suau, Elena Congeduti, Rolf A.N. Starre, Aleksander Czechowski and Frans A. Oliehoek
Influence Based Abstraction in Deep Reinforcement Learning
12:15 - 12:30 Short Talk: Aleksandra Malysheva, Aleksei Shpilman and Daniel Kudenko
MAGNet: Multi-agent Graph Network for Deep Multi-agentReinforcement Learning
12:30 - 14:00 Lunch
14:00 - 15:30 Session III - Chair: Felipe Leno Da Silva
14:00 - 14:30
Long Talk: Johan Källström and Fredrik Heintz
Tunable Dynamics in Agent-Based Simulation using Multi-Objective Reinforcement Learning (Best Paper Award Winner)
14:30 - 15:00
Long Talk: Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers and Ann Nowé
Equilibria in Multi-Objective Games: a Utility-Based Perspective
15:00 - 15:15
Short Talk: Mathieu Reymond and Ann Nowé
Pareto-DQN: Approximating the Pareto front in complex multi-objective decision problems
15:15 - 15:30
Short Talk: Ruiyang Xu and Karl Lieberherr
Learning Self-Game-Play Agents for Combinatorial Optimization Problems
15:30 - 16:00 Coffee Break
16:00 - 18:00 Poster Session A
19:00 - ... ALA Social Event
The ALA social event will be held at the Hurley's Irish Pub. Here is the location:

Tuesday 14 May (Location: Room MB 9B)

09:00 - 10:30 Session IV - Chair: Roxana Rădulescu
09:00 - 09:30 Contributed Talk: Julian Garcia
No winning strategy in the Iterated Prisoner's Dilemma: Game Theory and Simulated Evolution
09:30 - 10:00
Long Talk: Daan Bloembergen and Fernando Santos
Moderate Responder Committees Maximize Fairness in (NxM)-Person Ultimatum Games
10:00 - 10:15 Short Talk: Panayiotis Danassis, Aris Filos-Ratsikas and Boi Faltings
Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior
10:15 - 10:30 Short Talk: David Mguni
Efficient Reinforcement Dynamic Mechanism Design
10:30 - 11:00 Coffee Break
11:00 - 12:30 Session V - Chair: Pieter Libin
11:00 - 11:30
Long Talk: Koji Fukuda
Autonomous Distributed System using Graph Convolutional Network
11:30 - 12:00
Long Talk: Vera Kazakova and Gita Sukthankar
Adaptable decentralized task allocation for hierarchically-defined domains
12:00 - 12:15 Short Talk: Farzaneh Shoeleh, Mohammadmehdi Yadollahi and Masoud Asadpour
Domain Adaptation based Transfer Learning using Adversarial Network
12:15 - 12:30 Short Talk: Gabriel Ramos, Roxana Rădulescu and Ann Nowé
A Budged-Balanced Tolling Scheme for Efficient Equilibria under Heterogeneous Preferences
12:30 - 14:00 Lunch
14:00 - 15:30 Session VI - Chair: Patrick MacAlpine
14:00 - 14:15
Short Talk: Pieter Libin, Timothy Verstraeten, Diederik Roijers, Wenjia Wang, Kristof Theys and Ann Nowé
Boundary Focused Thompson Sampling
14:15 - 14:30
Short Talk: Keiichi Namikoshi and Sachiyo Arai
Estimation of agent's rewards using multi-agent maximum discounted causal entropy inverse reinforcement learning
14:30 - 14:45
Short Talk: Brian Broll, Matthew Hausknecht and Adith Swaminathan
Customizing Scripted Bots: Sample Efficient Imitation Learning for Human-like Behavior in Minecraft
14:45 - 15:00
Short Talk: Arno Moonens and Ann Nowé
Fine-grained control of electric vehicle charging with policy gradient
15:00 - 15:30
Awards, closing remarks and ALA 2020
15:30 - 16:00 Coffee Break
16:00 - 18:00 Poster Session B

Poster sessions

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

Papers presented in Sessions I - III together with:

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

Papers presented in Sessions IV - VI together with:

Invited Talk

Garrett Warnell

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


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,, 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


This year's workshop is organised by: Senior Steering Committee Members:
  • 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)


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

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