A self-adaptive neural learning classifier system with constructivism for mobile robot control

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3242, Issue , 2004, Pages 942-951

  Hurst, Jacob ^a   Bull, Larry ^a  

^a UNIVERSITY OF THE WEST OF ENGLAND   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; COMPLEX NETWORKS; LEARNING ALGORITHMS; MOBILE ROBOTS; NEURAL NETWORKS; PROBLEM SOLVING;

COMPLEX LIFE; MOBILE ROBOT CONTROL; MOBILE ROBOT PLATFORMS; NEURAL LEARNING; RULE COMPLEXITY; SELF ADAPTATION; SYSTEM USE;

LEARNING SYSTEMS;

EID: 35048891595     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30217-9_95     Document Type: Article

References (23)

1. Quartz, S.R & Sejnowski, T.J. (1997) The Neural Basis of Cognitive Development: A Constructionist Manifesto. Behavioural and Brain Sciences 20(4): 537-596.
2. Edelman, G. (1987) Neural Darwinism: The Theory of Neuronal Group Selection. Basic.
3. Holland, J.H. (1976) Adaptation. In R. Rosen & P.M. Snell (eds) Progress in Theoretical Biology 4. Academic Press, pp263-293.
4. Bull, L. (2002) On using Constructivism in Neural Learning Classifier Systems. In J. Merelo, P. Adamidis, H.G. Beyer, J-L. Fernandez-Villacanas & H-P. Schwefel (eds) Parallel Problem Solving from Nature - PPSN VII. Springer Verlag, pp558-567
5. Farmer, D. (1989) A Rosetta Stone for Connectionism. Physica D 42:153-187.
6. Davis, L. (1989) Mapping Neural Networks into Classifier Systems. In J.D. Schaffer (ed.) Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, pp375-378.
7. Schuurmans, D. & Schaeffer, J. (1989) Representational Difficulties with Classifier Systems. In J.D. Schaffer (ed.) Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, pp328-333.
8. Holland, J.H. (1975) Adaptation in Natural and Artificial Systems. Univ. Michigan Press.
9. Yao, X. (1999) Evolving Artificial Neural Networks. Proceedings of the IEEE 87(9): 1423-1447.
10. Moriarty, D.E. & Miikulainen, R. (1997) Forming Neural Networks Through Efficient and Adaptive Coevolution. Evolutionary Computation 5(2): 373-399.
11. Hurst, J., Bull, L. & Melhuish, C. (2002) TCS Learning Classifier System Controller on a Real Robot. In J. Merelo, P. Adamidis, H-G. Beyer, J-L. Fernandez-Villacanas & H-P. Schwefel (eds) Parallel Problem Solving from Nature - PPSN VII. Springer Verlag, pp588-600.
12. Wilson, S.W. (1994) ZCS: A Zeroth-level Classifier System. Evolutionary Computation 2(1):1-18.
13. Bull, L. & Hurst, J. (2002) ZCS Redux. Evolutionary Computation 10(2): 185-205
14. Poggio, T. & Girosi, F. (1990) Networks for approximation and learning Proceedings of the IEEE, 78: 1481-1497.
15. Parr, R. (1998) Hierarchical Control and Learning for Markov Decision Processes. PhD Thesis, University of California, Berkeley.
16. Santamaria, J.C., Sutton, R. & Ram, A. (1998) Experiments in Reinforcement Learning in Problems with Continuous State and Action Spaces. Adaptive Behaviour 6(2): 163-217.
17. Baeck, T. (1995) Evolutionary Computation: Theory and Practice. Oxford.
18. Montana, D.J. & Davis, L. (1989) Training Feedforward Neural Networks using Genetic Algorithms. In S. Sridharan (ed) Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Morgan Kauffman, pp762-767.
19. Dorigo, M. & Colombetti, M. (1997) Robot Shaping. MIT Press.
20. Sutton, R.S. & Barto, R. (1998) Reinforcement Learning. MIT Press.
21. Nolfi, S. & Floreano, D. (2000) Evolutionary Robotics: Biology, Intelligence, and Technology of Self-Organizing Machines. MIT Press.
22. O'Hara, T. & Bull, L. (2003) Backpropagation in Accuracy-based Neural Learning Classifier Systems. UWE Learning Classifier Systems Croup Technical Report - UWELCSG03-007. Available from http://www.cems.uwe.ac.uk/lcsg
23. Bull, L. & O'Hara, T. (2002) Accuracy-based Neuro and Neuro-Fuzzy Classifier Systems. In W.B.Langdon, E.Cantu-Paz, K.Mathias, R. Roy, D.Davis, R. Poli, K.Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A.C. Schultz, J. F. Miller, E. Burke & N.Jonoska (eds) Proceedings of the Genetic and Evolutionary Computation Conference - GECCO-02. Morgan Kaufmann, pp905-911.