Abstract
An evolutionary algorithm for the creation of recurrent network structures is presented. The aim is to develop neural networks controlling the behaviour of miniature robots. Two different tasks are solved with this approach. For the first, the agents are required to move within an environment without colliding with obstacles. In the second task, the agents are required to move towards a light source. The evolution process is carried out in a simulated environment and individuals with high performance are also tested on a physical environment with the use of Khepera robots.
Cite
CITATION STYLE
Hülse, M., Lara, B., Pasemann, F., & Steinmetz, U. (2001). Evolving neural behaviour control for autonomous robots. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 957–962). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_132
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
