Learning a Fuzzy Control with an Adaptive Representation

von Antony Waldock

176 Seiten, Hardcover

Kurzbeschreibung des Verlags

Programming an autonomous robot to operate in a real-world environment is extremely challenging. Machine learning techniques are seen as a promising alternative to the reliance on building accurate models of the robot platform and its environment by learning a controller while on the robot platform in the real environment. Currently, the majority of machine learning techniques applied to learning a robot controller use a uniform or pre-defined internal representation provided by a human designer. A uniform representation typically provides poor generalisation for control applications, and a pre-defined representation requires the designer to have an in-depth knowledge of the desired control policy. In this thesis, the approach taken is to reduce the reliance on a human designer by adapting the internal representation, to improve the generalisation over the control policy, during the learning process.

• Themen: Informatik und Informationstechnologie Allgemeine Themen
• ISBN: 9781447810001
• Sprache: Englisch
• Erscheinungsdatum: 17.11.2007
• Größe: 235 x 157 mm
• Verlag: Lulu Press, Inc.