The role of non-linearity for evolved multifunctional robot behavior

Authors:
Martin Hülse;Steffen Wischmann;Frank Pasemann
Affiliations:
Fraunhofer Institute, Autonomous Intelligent Systems, Sankt Augustin, Germany;Fraunhofer Institute, Autonomous Intelligent Systems, Sankt Augustin, Germany;Fraunhofer Institute, Autonomous Intelligent Systems, Sankt Augustin, Germany
Venue:
ICES'05 Proceedings of the 6th international conference on Evolvable Systems: from Biology to Hardware
Year:
2005

Citing 5
Cited 1

Characterization of periodic attractors in neural ring networks

Neural Networks
Being There: Putting Brain, Body, and World Together Again

Being There: Putting Brain, Body, and World Together Again
Evolutionary Robotics: The Biology,Intelligence,and Technology

Evolutionary Robotics: The Biology,Intelligence,and Technology
Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms

The 3rd International Symposium on Experimental Robotics III
A dynamical systems perspective on agent-environment interaction

Artificial Intelligence

Brain Organization and Computation

IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper the role of non-linear control structures for the development of multifunctional robot behavior in a self-organized way is discussed. This discussion is based on experiments where combinations of two behavioral tasks are incrementally evolved. The evolutionary experiments develop recurrent neural networks of general type in a systematically way. The resulting networks are investigated according to the underlying structure-function relations. These investigations point to necessary properties providing multifunctionality, scalability, and open-ended evolutionary strategies in Evolutionary Robotics.