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Learning a robot controller using an adaptive hierarchical fuzzy rule-based system (2015)
Journal Article
Waldock, A., & Carse, B. (2016). Learning a robot controller using an adaptive hierarchical fuzzy rule-based system. Soft Computing, 20(7), 2855-2881. https://doi.org/10.1007/s00500-015-1688-3

© 2015, Springer-Verlag Berlin Heidelberg. The majority of machine learning techniques applied to learning a robot controller generalise over either a uniform or pre-defined representation that is selected by a human designer. The approach taken in t... Read More about Learning a robot controller using an adaptive hierarchical fuzzy rule-based system.

Fuzzy classifier system architectures for mobile robotics: An experimental comparison (2007)
Journal Article
Carse, B., Pipe, A. G., Pipe, A. G., & Carse, B. (2007). Fuzzy classifier system architectures for mobile robotics: An experimental comparison. International Journal of Intelligent Systems, 22(9), 993-1019. https://doi.org/10.1002/int.20235

We present an experimental comparison between two approaches to optimization of the rules for a fuzzy controller. More specifically, the problem is autonomous acquisition of an "investigative" obstacle avoidance competency for a mobile robot. We repo... Read More about Fuzzy classifier system architectures for mobile robotics: An experimental comparison.

Fuzzy-XCS: A Michigan genetic fuzzy system (2007)
Journal Article
Casillas, J., Carse, B., & Bull, L. (2007). Fuzzy-XCS: A Michigan genetic fuzzy system. IEEE Transactions on Fuzzy Systems, 15(4), 536-550. https://doi.org/10.1109/TFUZZ.2007.900904

The issue of finding fuzzy models with an interpretability as good as possible without decreasing the accuracy is one of the main research topics on genetic fuzzy systems. When they are used to perform online reinforcement learning by means of Michig... Read More about Fuzzy-XCS: A Michigan genetic fuzzy system.

Hierarchical fuzzy rule based systems using an information theoretic approach (2006)
Journal Article
Waldock, A., Carse, B., & Melhuish, C. (2006). Hierarchical fuzzy rule based systems using an information theoretic approach. Soft Computing, 10(10), 867-879. https://doi.org/10.1007/s00500-005-0013-y

This paper proposes a novel anytime algorithm for the construction of a Hierarchical Fuzzy Rule Based System using an information theoretic approach to specialise rules that do not effectively model the decision space. The amount of uncertainty toler... Read More about Hierarchical fuzzy rule based systems using an information theoretic approach.

Application of Multi-Agent Technology to Fault Diagnosis of Power Distribution Systems (2005)
Journal Article
Yang, J., Montakhab, M., Pipe, A. G., Carse, B., & Davies, T. S. (2005). Application of Multi-Agent Technology to Fault Diagnosis of Power Distribution Systems. International Journal of Intelligent Information Technologies, 1(2), 1-16. https://doi.org/10.4018/jiit.2005040101

When a fault occurs in a power system, the protective relays detect the fault and trip appropriate circuit breakers, which isolate the affected equipment from the rest of the power system. Fault diagnosis of power systems is the process of identifyin... Read More about Application of Multi-Agent Technology to Fault Diagnosis of Power Distribution Systems.