ERLARS 2011 - 4th International Workshop on
Evolutionary and Reinforcement Learning for Autonomous Robot Systems


Please note: This page is about a past workshop. Please look at our main page for information on current and upcoming events.

Call for Papers

The call for papers can be downloaded as a PDF file here.
Learning is essential for an autonomous robot system. The range of unexpected situations it can handle while performing its task depends on its ability to adapt. Recent developments have taken autonomous robots beyond industrial settings, for example at home as toys and cleaners. However, production models usually interact with their environment following a fixed control strategy, which limits their range of application. More adaptable robots require control strategies that learn more and better from interactions with their environment.
The ERLARS workshop addresses the challenge to develop efficient and versatile learning architectures for autonomous robot systems, with the main focus on adequate evolutionary and reinforcement learning algorithms.

Relevant Topics

Papers are invited on all aspects of learning methods for the control of autonomous robot systems, including, but not limited to:

Submission Schedule

Paper format

All articles will be published both in a proceedings book with an ISSN, as well as online. Please see the authors' section for formatting instructions.

Author of these pages: Nils T Siebel.
Last modified on Wed Mar 7 2012.
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