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.
About this Workshop
Evolutionary and Reinforcement Learning methods are important learning approaches for neural networks and other knowledge representations. They are inspired by nature and known to be used extensively in biological systems. However, so far their use in artificial cognitive systems, e.g. autonomous robot systems, is limited. This is mainly due to the large number of necessary robot actions and/or learning cycles before an acceptable mapping from perceptions to actions is found. Autonomous robots are becoming more and more common even in non-industrial settings, an example area being toys like Sony's Aibo robotic dog and the new Pleo toy dinosaur. However, they tend to have very limited learning capabilities. These are usually restricted to adjusting a few parameters in an otherwise fixed control strategy that determines how the robot interacts with the environment.
In recent years, fast computers have made evolutionary and reinforcement learning more feasible from a computational point of view. Therefore research in these areas has attracted more attention. A number of new and efficient algorithms have shown promising results, albeit many of these still rely on training in simulated environments or in combinations of offline and online learning.
The main goal of this workshop is to bring together researchers and promote work on evolutionary and reinforcement learning methods with a focus on their (future) application in autonomous robot systems. We believe that in order to achieve this a great deal of fundamental research, e.g. on the efficiency of algorithms, is just as important as their practical applications. Therefore contributions are invited both on theoretical and practical results in this area.
The workshop topics include, but are not limited to:
- Model-free visual servoing
- Mobile robot navigation by means of reinforcement learning
- Combining offline- and online learning methods for robot control
- Reinforcement learning by evolutionary algorithms of neural network- based and other robot controllers
- Hybrid systems that combine modelling and parameter estimation by reinforcement learning
- Learning from scratch and cascaded learning architectures
- Knowledge-based reinforcement learning
- Developmental and epigenetic robotics
- Balancing exploration and exploitation of acquired knowledge
- Simulated environments for autonomous robot learning scenarios
Location and Dates
The 4th ERLARS workshop, ERLARS 2011, will take place in Berlin, Germany on Friday/Saturday, December 9/10 2011 at the HTW University of Applied Sciences Berlin.
- October 16 2011: Paper submissions due
- November 4 2011: Notification of paper acceptance
- November 15 2011: Camera ready paper submission
- November 15 2011: Early registration/Workshop registration for presenting author
- December 9/10 2011: Workshop takes place
Nils T Siebel
Department of Engineering 1
HTW University of Applied Sciences Berlin
Research Group Robotics
University of Bremen
Author of these pages: Nils T Siebel.
Last modified on Wed Mar 7 2012.
Last modified on Wed Mar 7 2012.