Generating Adaptive Behavior for a Real Robot using Function Regression within Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7964

@InProceedings{banzhaf:1997:gabrrfr,

• author = "Wolfgang Banzhaf and Peter Nordin and Markus Olmer",
• title = "Generating Adaptive Behavior for a Real Robot using Function Regression within Genetic Programming",
• booktitle = "Genetic Programming 1997: Proceedings of the Second Annual Conference",
• editor = "John R. Koza and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max Garzon and Hitoshi Iba and Rick L. Riolo",
• year = "1997",
• month = "13-16 " # jul,
• keywords = "genetic algorithms, genetic programming",
• pages = "35--43",
• address = "Stanford University, CA, USA",
• publisher_address = "San Francisco, CA, USA",
• publisher = "Morgan Kaufmann",
• URL = "http://www.cs.mun.ca/~banzhaf/papers/robot_over.pdf",
• size = "11 pages",
• abstract = "We discuss the generation of adaptive behaviour for an autonomous robot within the framework of a special kind of function regression used in compiling Genetic Programming (GP). The control strategy for the robot is derived, using an evolutionary algorithm, from a continuous improvement of machine language programs which are varied and selected against each other. We give an overview of our recent work on several fundamental behaviors like obstacle avoidance and object following adapted from programs that were originally random sequences of commands. It is argued that the method is generally applicable where there is a need for quick adaptation within real-time problem domains",
• notes = "GP-97",

}

Genetic Programming entries for Wolfgang Banzhaf Peter Nordin Markus Olmer

Citations