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)
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