Cogprints

Evolution of Neural Networks for Helicopter Control: Why Modularity Matters

De Nardi, Renzo and Togelius, Julian and Holland, Owen and Lucas, Simon M. (2006) Evolution of Neural Networks for Helicopter Control: Why Modularity Matters. [Conference Paper]

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Abstract

The problem of the automatic development of controllers for vehicles for which the exact characteristics are not known is considered in the context of miniature helicopter flocking. A methodology is proposed in which neural network based controllers are evolved in a simulation using a dynamic model qualitatively similar to the physical helicopter. Several network architectures and evolutionary sequences are investigated, and two approaches are found that can evolve very competitive controllers. The division of the neural network into modules and of the task into incremental steps seems to be a precondition for success, and we analyse why this might be so.

Item Type:Conference Paper
Subjects:Computer Science > Machine Learning
Computer Science > Neural Nets
Computer Science > Robotics
ID Code:5222
Deposited By:Togelius, Julian
Deposited On:15 Oct 2006
Last Modified:11 Mar 2011 08:56

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