Further comparison between ATNoSFERES and XCSM

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

Volumn 2661, Issue , 2003, Pages 99-117

  Landau, Samuel ^a   Picault, Sébastien ^b   Sigaud, Olivier ^a   Gérard, Pierre ^a  

^a UNIVERSITÉ PIERRE ET MARIE CURIE   (France)

^b ECOLE CENTRALE DE LILLE   (France)

Author keywords

ATN1; Evolutionary algorithms; Internal state generalization; Learning classifier systems; Perceptual aliazing

Indexed keywords

CLUSTERING ALGORITHMS; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHMS; CONTROL SYSTEMS; DATA STORAGE EQUIPMENT; ENCODING (SYMBOLS); FINITE AUTOMATA;

ATN^1; BENCHMARK EXPERIMENTS; INDIRECT ENCODING; INTERNAL STATE; LEARNING CLASSIFIER SYSTEM; MEMORY-BASED EXTENSION; PERCEPTUAL ALIAZING;

LEARNING SYSTEMS; GENETIC ALGORITHMS;

FINITE-STATE AUTOMATA CONTROLLERS; INTERNAL STATE GENERALIZATION; MEMORY-BASED EXTENSION; PERCEPTUAL ALIAZING;

EID: 0346955730     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-40029-5_7     Document Type: Conference Paper

References (23)

1. K. A. DE JONG, An Analysis of the Behavior of a Class of Genetic Adaptive Systems, PhD thesis, Dept. of Computer and Communication Sciences, University of Michigan, 1975.
2. L. J. FOGEL, A. J. OWENS, and M. J. WALSH, Artificial Intelligence through Simulated Evolution, John Wiley & Sons, 1966.
3. D. E. GOLDBERG, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
4. F. GRUAU, Neural Network Synthesis Using Cellular Encoding and the Genetic Algorithm, Ph.D. thesis, ENS Lyon–Université Lyon I, 1994.
5. J. H. HOLLAND, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press, Ann Arbor, MI, 1975.
6. J. KODJABACHIAN and J.-A. MEYER, Evolution and Development of Neural Controllers for Locomotion, Gradient-Following, and Obstacle-Avoidance in Artificial Insects, IEEE Transactions on Neural Networks, 9 (1998), pp. 796–812.
7. J. R. KOZA, Genetic Programming: On the Programming of Computers byMeans of Natural Selection, MIT Press, Cambridge, MA, 1992.
8. J. R. KOZA, F. H. BENNETT III, D. ANDRE, and M. A. KEANE, Automated Design of Both the Topology and Sizing of Analog Electrical Circuits Using Genetic Programming, in Artificial Intelligence in Design’96, J. S. Gero and F. Sudweeks, eds., 1996, pp. 151–170.
9. S. LANDAU and S. PICAULT, Stack-Based Gene Expression, Technical Report LIP6 2002/011, LIP6, Paris, 2002.
10. S. LANDAU, S. PICAULT, and A. DROGOUL, ATNoSFERES: a Model for Evolutive Agent Behaviors, in Proceedings of the AISB’01 Symposium on Adaptive Agents and Multi-Agent Systems, 2001.
11. S. LANDAU, S. PICAULT, O. SIGAUD, and P. GéRARD, A Comparison between ATNoSFERES and XCSM, in Proc. of the Genetic and Evolutionary Computation Conference (GECCO 2002), W. 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. Schultz, J. F.Miller, E. Burke, and N. Jonoska, eds., New York, july 9-13 2002, Morgan Kaufmann, pp. 926–933.
12. P. L. LANZI, An Analysis of the Memory Mechanism of XCSM, in Proceedings of the Third Annual Conference on Genetic Programming, J. R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D. B. Fogel, M. H. Garzon, D. E. Goldberg, H. Iba, and R. Riolo, eds., University of Wisconsin, Madison, Wisconsin, USA, 1998, Morgan Kaufmann.
13. A. LINDENMAYER, Mathematical Models for Cellular Interaction in Development, parts I and II, Journal of theoretical biology, 18 (1968).
14. S. LUKE and L. SPECTOR, Evolving Graphs and Networks with Edge Encoding: Preliminary Report, in Late Breaking Papers at the Genetic Programming 1996 Conference, J. R. Koza, ed., Stanford University, CA, july 1996, Stanford Bookstore, pp. 117–124.
15. D. J. MONTANA, Strongly Typed Genetic Programming, in Evolutionary Computation, Vol. 3, 1995.
16. S. PICAULT and S. LANDAU, Ethogenetics and the Evolutionary Design of Agent Behaviors, in Proceedings of the 5th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI’01), N. Callaos, S. Esquivel, and J. Burge, eds., Vol. III, 2001, pp. 528–533.
17. H.-P. SCHWEFEL, Evolution and Optimum Seeking, John Wiley and Sons, Inc., 1995.
18. R. S. SUTTON and A. G. BARTO, Reinforcement Learning, an introduction, MIT Press, Cambridge, MA, 1998.
19. A. TOMLINSON and L. BULL, CXCS, in Learning Classifier Systems: from Foundations to Applications, P. Lanzi, W. Stolzmann, and S. Wilson, eds., Springer Verlag, Heidelberg, 2000, pp. 194–208.
20. S. W. WILSON, ZCS, a Zeroth level Classifier System, Evolutionary Computation, 2 (1994), pp. 1–18.
21. S. W. WILSON, Classifier Fitness Based on Accuracy, Evolutionary Computation, 3 (1995), pp. 149–175.
22. W. A. WOODS, Transition Networks Grammars for Natural Language Analysis, Communications of the Association for the Computational Machinery, 13 (1970), pp. 591–606.
23. X. YAO, Evolving Artificial Neural Networks, Proceedings of the IEEE, 87 (1999).