A Reward-Value Based Constructive Method for the Autonomous Creation of Machine Controllers

Authors:
Andreas Huemer;David Elizondo;Mario Gongora
Affiliations:
Institute Of Creative Technologies, De Montfort University, Leicester, UK;Centre for Computational Intelligence, De Montfort University, Leicester, UK;Centre for Computational Intelligence, De Montfort University, Leicester, UK
Venue:
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Year:
2008

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Abstract

A novel method for the creation of machine controllers autonomously is presented. The method is based on reward values which can represent the internal state of the machine or the rating of its task performance. The method consists of a biologically sound constructive neural network model with a minimum number of neurons and no connections initially. New connections and neurons are added when feedback is fed into the neural network using positive and negative reward values. This way the topology and the level of connectivity of the network are kept to a minimum. The method will be applied to a controller for an autonomous mobile robot.