At the same time, multi-agent learning poses significant theoretical challenges, particularly in understanding how agents can learn and adapt in the presence of other agents that are simultaneously learning and adapting. This is a fertile area of research that seems ripe for progress: the numerous and significant theoretical developments of the 1990s, in fields such as Bayesian, game-theoretic, decision-theoretic, and evolutionary learning, can now be extended to more challenging multi-agent scenarios.
This workshop on multi-agent learning is intended to be broad in scope and informal in style. The goal is to bring together researchers from a variety of perspectives in multi-agent learning who would likely benefit from open communications, comparing methodologies and sharing insights into recent results, common challenges, and future opportunities for progress.
In keeping with our desire to have a loose and lively workshop, there will be no formal paper submissions or published proceedings. There will be numerous short talks - mainly by invited speakers, but also some slots for contributed talks - and plenty of time for open discussion. A novel aspect of this workshop, intended to stimulate discussion, is that two of the invited talks will survey highlights of two other upcoming workshops on multi-agent systems (at ICMAS and ECML).
Researchers who are interested in attending the workshop can help us project expected attendance by sending email to the organizers at the addresses given below.