Adaptive 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 fourteenth year. Previous editions of this workshop may be found at the following urls:
The goal of this workshop is to increase
awareness 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 multiagent systems. It aims at bringing together not
only scientists from different areas of
computer science (e.g., agent architectures,
reinforcement learning, and 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 on ongoing or
completed work in both theoretical and
practical issues of adaptive and learning
agents and multiagent systems.
This workshop will focus on all
aspects of adaptive and learning agents
and multiagent 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 multiagent learning
- Reinforcement learning (single and multiagent)
- Planning (single and multiagent)
- Reasoning (single and multiagent)
- Distributed learning
- Adaptation and learning in dynamic environments
- Evolution of agents in complex environments
- Co-evolution of agents in a multiagent setting
- Cooperative exploration and learning to cooperate and collaborate
- Learning trust and reputation
- Communication restrictions and their impact on multiagent 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 multiagent systems
- Game theoretical analysis of adaptive multiagent systems
- Neuro-control in multiagent systems
- Bio-inspired multiagent systems
- Applications of adaptive and learning
agents and multiagents systems to real
world complex systems
- Learning of Co-ordination
Accepted papers from the workshop will be eligible to be extended for inclusion in a special issue journal.
