Fast rule identification and neighborhood selection for cellular automata

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 41, Issue 3, 2011, Pages 749-760

  Sun, Xianfang ^a   Rosin, Paul L ^a   Martin, Ralph R ^a  

^a CARDIFF UNIVERSITY   (United Kingdom)

Author keywords

Cellular automata (CA); neighborhood selection; rule identification

Indexed keywords

BAYESIAN INFORMATION CRITERION; CA MODEL; EVOLUTION RULES; IDENTIFICATION ALGORITHMS; IDENTIFICATION PROBLEM; MINIMUM VARIANCE; NEIGHBORHOOD SELECTION; NEIGHBORHOOD SIZE; OBSERVED DATA; PARAMETER ESTIMATE; RULE EXTRACTION; RULE IDENTIFICATION; UNIFIED FRAMEWORK;

ALGORITHMS; CELLULAR AUTOMATA; IDENTIFICATION (CONTROL SYSTEMS); INVERSE PROBLEMS; MATHEMATICAL MODELS; PATTERN RECOGNITION SYSTEMS;

PARAMETER ESTIMATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; DECISION SUPPORT SYSTEM; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DECISION SUPPORT TECHNIQUES; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 79957518633     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2010.2091271     Document Type: Article

References (37)

1. A. Ilachinski, Cellular Automata: A Discrete Universe. River Edge, NJ: World Scientific, 2001.
2. J. von Neumann, "The general and logical theory of automata," in Cerebral Mechanisms in Behavior-The Hixon Symposium, L. Jeffress, Ed. New York: Wiley, 1951, pp. 1-31.
3. S. Wolfram, Cellular Automata and Complexity: Collected Papers. Boulder, CO: Westview, 1994.
4. S. Wolfram, A New Kind of Science. Champaign, IL: Wolfram Media Inc., 2002.
5. N. Ganguly, B. K. Sikdar, A. Deutsch, G. Canright, and P. P. Chaudhuri, "A survey on cellular automata," Centre High Perform. Comput., Dresden Univ. Technol., Dresden, Germany, Tech. Rep., Dec. 2003.
6. J. Shan, S. Alkheder, and J.Wang, "Genetic algorithms for the calibration of cellular automata urban growth modeling," Photogramm. Eng. Remote Sens., vol. 74, no. 10, pp. 1267-1277, Oct. 2008.
7. E. Sapin, L. Bull, and A. Adamatzky, "Genetic approaches to search for computing patterns in cellular automata," IEEE Comput. Intell. Mag., vol. 4, no. 3, pp. 20-28, Aug. 2009.
8. P. L. Rosin, "Image processing using 3-state cellular automata," Comput. Vis. Image Understanding, vol. 114, no. 7, pp. 790-802, Jul. 2010.
9. N. Packard, "Adaptation toward the edge of chaos," in Dynamic Patterns in Complex Systems, J. Kelso, A. Mandell, and M. Shlesinger, Eds. Singapore: World Scientific, 1989, pp. 293-301.
10. F. C. Richards, T. P. Meyer, and N. H. Packard, "Extracting cellular automaton rules directly from experimental data," Phys. D, vol. 45, no. 1-3, pp. 189-202, Sep. 1990.
11. M. Mitchell, J. P. Crutchfield, and R. Das, "Evolving cellular automata with genetic algorithms: A review of recent work," in Proc. 1st Int. Conf. EvCA, 1996.
12. Y. Yang and S. Billings, "Extracting Boolean rules from CA patterns," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 30, no. 4, pp. 573-580, Aug. 2000.
13. Z. Pan and J. Reggia, "Artificial evolution of arbitrary self-replicating structures," J. Cellular Automata, vol. 1, no. 2, pp. 105-123, 2006.
14. P. Rosin, "Training cellular automata for image processing," IEEE Trans. Image Process., vol. 15, no. 7, pp. 2076-2087, Jul. 2006. (Pubitemid 43985083)
15. A. Adamatzky, Identification of Cellular Automata. London, U.K.: Taylor & Francis, 1994.
16. A. Adamatzky, "Automatic programming of cellular automata: Identification approach," Kybernetes: Int. J. Syst. Cybern., vol. 26, no. 2, pp. 126-135, Feb. 1997. (Pubitemid 127362181)
17. K.-I. Maeda and C. Sakama, "Identifying cellular automata rules," J. Cellular Automata, vol. 2, no. 1, pp. 1-20, 2007.
18. Y. Zhao and S. Billings, "The identification of cellular automata," J. Cellular Automata, vol. 2, no. 1, pp. 47-65, 2007.
19. Y. Yang and S. Billings, "Neighborhood detection and rule selection from cellular automata patterns," IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 30, no. 6, pp. 840-847, Nov. 2000. (Pubitemid 32169096)
20. S. Billings and Y. Yang, "Identification of probabilistic cellular automata," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 33, no. 2, pp. 225-236, Apr. 2003.
21. S. Billings and Y. Yang, "Identification of the neighborhood and CA rules from spatio-temporal CA patterns," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 33, no. 2, pp. 332-339, Apr. 2003.
22. S. A. Billings and S. S. Mei, "A new fast cellular automata orthogonal least-squares identification method," Int. J. Syst. Sci., vol. 36, no. 8, pp. 491-499, Jun. 2005. (Pubitemid 41663586)
23. F. Ding, Y. Shi, and T. Chen, "Auxiliary model-based least-squares identification methods for Hammerstein output-error systems," Syst. Control Lett., vol. 56, no. 5, pp. 373-380, May 2007. (Pubitemid 46435731)
24. F. Ding, L. Qiu, and T. Chen, "Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems," Automatica, vol. 45, no. 2, pp. 324-332, Feb. 2009.
25. F. Ding, P. X. Liu, and G. Liu, "Multiinnovation least-squares identification for system modeling," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 40, no. 3, pp. 767-778, Jun. 2010.
26. F. Ding, P. X. Liu, and G. Liu, "Gradient based and least-squares based iterative identification methods for OE and OEMA systems," Dig. Signal Process., vol. 20, no. 3, pp. 664-677, May 2010.
27. F. Ding, G. Liu, and X. Liu, "Partially coupled stochastic gradient identification methods for non-uniformly sampled systems," IEEE Trans. Autom. Control, vol. 55, no. 8, pp. 1976-1981, Aug. 2010.
28. L. He and X. Sun, "Recursive triangulation description of the feasible parameter set for bounded-noise models," IET Control Theory Appl., vol. 4, no. 6, pp. 985-992, Jun. 2010.
29. H.-F. Chen, "New approach to recursive identification for ARMAX systems," IEEE Trans. Autom. Control, vol. 55, no. 4, pp. 868-879, Apr. 2010.
30. S. Mei, S. A. Billings, and L. Guo, "A neighborhood selection method for cellular automata models," Int. J. Bifurcation Chaos, vol. 15, no. 2, pp. 383-393, 2005. (Pubitemid 40661901)
31. Y. Zhao and S. Billings, "Neighborhood detection using mutual information for identification of cellular automata," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 36, no. 2, pp. 473-479, Apr. 2006.
32. Y. Guo, S. A. Billings, and D. Coca, "Identification of n-state spatiotemporal dynamical systems using a polynomial model," Int. J. Bifurcation Chaos, vol. 18, no. 7, pp. 2049-2057, 2008.
33. L. Guo, S. Mei, and S. Billings, "Neighbourhood detection and identification of spatio-temporal dynamical systems using a coarse-to-fine approach," Int. J. Syst. Sci., vol. 38, no. 1, pp. 1-15, Jan. 2007. (Pubitemid 46012682)
34. M. Esnaashari and M. Meybodi, "A cellular learning automata based clustering algorithm for wireless sensor networks," Sens. Lett., vol. 6, no. 5, pp. 723-735, Oct. 2008.
35. H. Akaike, "A new look at the statistical model identification, " IEEE Trans. Autom. Control, vol. AC-19, no. 6, pp. 716-723, Dec. 1974.
36. G. Schwarz, "Estimating the dimension of a model," Ann. Statist., vol. 6, no. 2, pp. 461-464, Mar. 1978.
37. K. Mao, "Fast orthogonal forward selection algorithm for feature subset selection," IEEE Trans. Neural Netw., vol. 13, no. 5, pp. 1218-1224, Sep. 2002.