Hybrid Control of Autonomous Systems

International Workshop on
Hybrid Control of Autonomous Systems
Integrating Learning, Deliberation and Reactive Control

Call for Papers
Journal of Robotics and Autonomous Systems
Special Issue on Hybrid Control of Autonomous Systems

Aims and Objectives

High-level control for Autonomous Systems (e.g. robots) is concerned with selecting the next action the system should perform. In particular this means that the system must be endowed with algorithms or schemes to take the next step towards its mission goal. The known paradigms for this action selection problem are learning, deliberation, reactive control schemes or combinations of these schemes, i.e. hybrid approaches.
Learning has been applied successfully to many robotics tasks. Most of the work is related to learning certain basic behaviours or skills. Examples where the high-level control strategy of robots (or agents) were successfully learned are rare. The deliberative approach for decision making of autonomous systems was successfully treated in research on Artificial Intelligence, following a top-down approach, which has severe limitations in real applications. In the reactive control paradigm the idea is that through a combination of purely reactive action selection schemes intelligent and goal-directed behaviours emerge, which can be seen as a bottom-up approach.
These paradigms have been known for over two decades, and in today's applications often combinations of learning, deliberation, and reactive control are used. Usually these combinations are used in an ad-hoc or even unconscious fashion. Although there is a number of proposed architectures and huge body of literature, the issue of combining learning, reactive and deliberative control never has been intensively investigated.
This special issue aims to survey a state of the art of hybrid systems and to compile a collection of the problems, the challenges, and the solutions of autonomous systems, i.e. robots or agent systems that make use of hybrid approaches for high-level control. A particular emphasis lies on the hybrid aspects of the presented approach.

Paper Submission

Areas of interest include (but are not restricted to) hybrid decision making, modelling of application domains which demands for hybrid control and related with this the required capabilities/affordances and needed robot behaviours. We solicit original work from the fields of Agent Learning, Cognitive Robotics, and Behaviour-based Control, deploying a hybrid approach for high-level control.
As a follow-up of the HYCAS workshop at the IJCAI-09 we invite in particular workshop participants to submit profoundly extended versions of their workshop submission, which suits this special issue. The call is nevertheless open to other interested researchers.
Papers should be typeset according to the format instructions for the Robotics and Autonomous Systems journal, available on the Elsevier web site. The length should not exceed 22 pages in the above format (single column). Other, non-standard formats (e.g., Word) cannot be accepted. In the body of the e-mail message, please specify the following:
All submissions will be acknowledged within a few days. Please contact the guest editors if you do not receive an acknowledgement.

Guest Editors

Alexander Ferrein
Robotics and Agents Research Lab
University of Cape Town, South Africa
Nils T Siebel
Building Automation Lab
HTW University of Applied Sciences Berlin, Germany
Gerald Steinbauer
Institute for Software Technology
Technical University of Graz, Austria

Important Dates


Author of these pages: Nils T Siebel.
Last modified on Thu Mar 18 2010.
Best Viewed With Any Browser!
Valid HTML 4.01!
Valid CSS!