Brian Carse - researchr alias

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Viewing Publication 1 - 42 from 42

2016

Learning a robot controller using an adaptive hierarchical fuzzy rule-based systemAntony Waldock, Brian Carse. soco, 20(7):2855-2881, 2016. [doi]

2013

Cooperative tabletop working for humans and humanoid robots: Group interaction with an avatarHamzah Z. Hossen Mamode, Paul Bremner, Anthony G. Pipe, Brian Carse. icra 2013: 184-190 [doi]

2012

Cooperative tabletop working for humans and humanoid robots: Early investigations into artifact indicationHamzah Z. Hossen Mamode, Paul Bremner, Tony Pipe, Brian Carse. coginfocom 2012: 231-236 [doi]

2009

Special issue on Genetic Fuzzy Systems: Recent Developments and Future Directions Jorge Casillas, Brian Carse. soco, 13(5):417-418, 2009. [doi]

2008

Fuzzy Q-Learning with an adaptive representationAntony Waldock, Brian Carse. fuzzIEEE 2008: 720-725 [doi]

2007

Introduction: Genetic fuzzy systemsBrian Carse, Anthony G. Pipe. ijis, 22(9):905-907, 2007. [doi]

Fuzzy-XCS: A Michigan Genetic Fuzzy SystemJorge Casillas, Brian Carse, Larry Bull. tfs, 15(4):536-550, 2007. [doi]

Fuzzy classifier system architectures for mobile robotics: An experimental comparisonAnthony G. Pipe, Brian Carse. ijis, 22(9):993-1019, 2007. [doi]

2006

Prediction of Failure in Pin-joints Using Hybrid Adaptive Neuro-Fuzzy ApproachShima Shirazi Kia, Siamak Noroozi, Brian Carse, John Vinney, Masoud Rabbani. fuzzIEEE 2006: 671-677 [doi]

Hierarchical fuzzy rule based systems using an information theoretic approachAntony Waldock, Brian Carse, Chris Melhuish. soco, 10(10):867-879, 2006. [doi]

2005

2004

Oneiric Processing Utilising the Anticipatory Classifier SystemJulian C. Holley, Anthony G. Pipe, Brian Carse. ppsn 2004: 1103-1112 [doi]

2003

2002

First Results from Experiments in Fuzzy Classifier System Architectures for Mobile RoboticsAnthony G. Pipe, Brian Carse. ppsn 2002: 578-587 [doi]

Experiments on a Pittsburgh-style fuzzy classifier system for mobile roboticsAnthony G. Pipe, Brian Carse, E. Malliris. IEEEisic 2002: 61-66 [doi]

2001

2000

A Note on Learning and Evolution in Neural NetworksBrian Carse, Johan Oreland. gecco 2000: 66-73

Evolution and Learning in Neural Networks: Dynamic Correlation, Relearning and ThresholdingBrian Carse, Johan Oreland. adb, 8(3-4):297-311, 2000. [doi]

Autonomous Acquisition of Fuzzy Rules for Mobile Robot Control: First Results from two Evolutionary Computation ApproachesAnthony G. Pipe, Brian Carse. gecco 2000: 849-856

1999

Connection Admission Control in ATM Networks Using Neural Networks: Research Directions and Issues in Commercial ExploitationPaul Cullen, Brian Carse. flairs 1999: 325-331

1998

Artificial evolution of fuzzy rule bases which represent time: A temporal fuzzy classifier systemBrian Carse, Terence C. Fogarty, Alistair Munro. ijis, 13(10-11):905-927, 1998. [doi]

Evolution and learning in neural networks. An experimental studyBrian Carse. SMC 1998: 2407-2412 [doi]

1997

Artificial evolution of fuzzy and temporal rule based systemsBrian Carse. PhD thesis, University of the West of England, Bristol, UK, 1997. [doi]

1996

Fast Evolutionary Learning of Minimal Radial Basis Function Neural Networks Using a Genetic AlgorithmBrian Carse, Terence C. Fogarty. aisb 1996: 1-22

Tackling the Curse of Dimensionality of Radial Basis Functional Neural Networks Using a Genetic AlgorithmBrian Carse, Terence C. Fogarty. ppsn 1996: 710-719

Evolving fuzzy rule based controllers using genetic algorithmsBrian Carse, Terence C. Fogarty, Alistair Munro. fss, 80(3):273-293, 1996. [doi]

1995

1994

A Delayed-Action Classifier System for Learning in Temporal EnvironmentsBrian Carse, Terence C. Fogarty. icec 1994: 670-673

Learning Anticipatory Behaviour Using a Delayed Action Classifier SystemBrian Carse. aisb 1994: 210-223

A Fuzzy Classifier System Using the Pittsburgh ApproachBrian Carse, Terence C. Fogarty. ppsn 1994: 260-269

A Comparison Between Two Architectures for Searching and Learning in Maze ProblemsAnthony G. Pipe, Brian Carse. aisb 1994: 238-249

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