[agents] 1st CFP: Thematic Issue on Algorithmic Reinforcement Learning

[Kostas Stathis]

[ Apologies for cross-posting]

Call For Papers: Thematic issue on "Algorithmic Reinforcement Learning"
Journal of Algorithms: Cognition, Informatics and Logic, Elsevier
Kostas Stathis, Artur d’Avilla Garcez, Robert Givan (Guest Editors)

Url: http://www.cs.rhul.ac.uk/~kostas/arl/cfp.html

This thematic issue of the Journal of Algorithms seeks to celebrate the 
increasingly
multidisciplinary nature of reinforcement learning and, in line with the 
Journal's
manifesto, it proposes to study and present the subject from an algorithmic
perspective that we refer to as Algorithmic Reinforcement Learning 
(ARL). It is
hoped that in this way this thematic volume will serve as a reference in 
the area and
will help organize and promote the research across sub-areas.

We welcome the submission of innovative and mature results in specifying,
developing and experimenting with ARL. Approaches that relate, compare and
contrast, combine or integrate different areas of reinforcement learning 
are
particularly encouraged. Papers describing innovative developments in 
the area are
also encouraged. Areas of interest include, but are not limited to the 
following topics:

• Multi-agent reinforcement learning
• Relational reinforcement learning
• Neuro-symbolic reinforcement learning
• Bayesian reinforcement learning
• Reinforcement learning and logic/ILP
• Reinforcement learning with background knowledge
• Robust reinforcement learning
• Reinforcement learning in game theory and bounded rationality
• Applications

Important Dates & Submission details

Submission Deadline: 1st Oct 2008
Acceptance Notice: 20th Jan 2009
Final Manuscript: 1st March 2009
Expected Publication Date: Summer 2009

-- 
Kostas Stathis                        kostas.stathis at rhul.ac.uk
Department of Computer Science        +44(0)1784 443698 (Tel)
Royal Holloway, University of London  +44(0)1784 439786 (Fax)
Egham, Surrey TW20 0EX, UK            http://www.cs.rhul.ac.uk/~kostas