Modular thinking: evolving modular neural networks for visual guidance of agents

This paper investigates whether replacing non-modular artificial neural network brains of visual agents with modular brains improves their ability to solve difficult tasks, specifically, survive in a changing environment. A set of experiments was conducted and confirmed that agents with modular brains are in fact better. Further analysis of the evolved modules characterised their function and determined their mechanism of operation. The results indicate that the greater survival ability is obtained due to functional specialisation of the evolved modules; good agents do well because their modules are more specialised at tasks such as reproduction and consumption. Overall, the more specialised the modules, the fitter the agents. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence General Terms Algorithms Keywords Modular Neural Networks, Multi-Agent Systems, Mosaic World

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Ehud Schlessinger, Peter J. Bentley, R. Beau Lotto
• Keywords: Evolved Modules, GECCO 2006, Modular Brains, Neural Network Brains, Optimization