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Identification of cellular automata based on incomplete observations with bounded time gaps

Witold Tadeusz Bolt, Jan Baetens (UGent) and Bernard De Baets (UGent)
(2020) IEEE TRANSACTIONS ON CYBERNETICS. 50(3). p.971-984
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Organization
Abstract
In this paper, the problem of identifying the cellular automata (CAs) is considered. We frame and solve this problem in the context of incomplete observations, i.e., prerecorded, incomplete configurations of the system at certain, and unknown time stamps. We consider 1-D, deterministic, two-state CAs only. An identification method based on a genetic algorithm with individuals of variable length is proposed. The experimental results show that the proposed method is highly effective. In addition, connections between the dynamical properties of CAs (Lyapunov exponents and behavioral classes) and the performance of the identification algorithm are established and analyzed.
Keywords
LYAPUNOV EXPONENTS, RULES, Table lookup, Genetic algorithms, Automata, Visualization, Cybernetics, Task analysis, Machine learning algorithms, Cellular automata (CAs), genetic algorithms (GAs), nonlinear dynamical systems, system identification

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MLA
Bolt, Witold Tadeusz, et al. “Identification of Cellular Automata Based on Incomplete Observations with Bounded Time Gaps.” IEEE TRANSACTIONS ON CYBERNETICS, vol. 50, no. 3, 2020, pp. 971–84, doi:10.1109/TCYB.2018.2875266.
APA
Bolt, W. T., Baetens, J., & De Baets, B. (2020). Identification of cellular automata based on incomplete observations with bounded time gaps. IEEE TRANSACTIONS ON CYBERNETICS, 50(3), 971–984. https://doi.org/10.1109/TCYB.2018.2875266
Chicago author-date
Bolt, Witold Tadeusz, Jan Baetens, and Bernard De Baets. 2020. “Identification of Cellular Automata Based on Incomplete Observations with Bounded Time Gaps.” IEEE TRANSACTIONS ON CYBERNETICS 50 (3): 971–84. https://doi.org/10.1109/TCYB.2018.2875266.
Chicago author-date (all authors)
Bolt, Witold Tadeusz, Jan Baetens, and Bernard De Baets. 2020. “Identification of Cellular Automata Based on Incomplete Observations with Bounded Time Gaps.” IEEE TRANSACTIONS ON CYBERNETICS 50 (3): 971–984. doi:10.1109/TCYB.2018.2875266.
Vancouver
1.
Bolt WT, Baetens J, De Baets B. Identification of cellular automata based on incomplete observations with bounded time gaps. IEEE TRANSACTIONS ON CYBERNETICS. 2020;50(3):971–84.
IEEE
[1]
W. T. Bolt, J. Baetens, and B. De Baets, “Identification of cellular automata based on incomplete observations with bounded time gaps,” IEEE TRANSACTIONS ON CYBERNETICS, vol. 50, no. 3, pp. 971–984, 2020.
@article{8655808,
  abstract     = {{In this paper, the problem of identifying the cellular automata (CAs) is considered. We frame and solve this problem in the context of incomplete observations, i.e., prerecorded, incomplete configurations of the system at certain, and unknown time stamps. We consider 1-D, deterministic, two-state CAs only. An identification method based on a genetic algorithm with individuals of variable length is proposed. The experimental results show that the proposed method is highly effective. In addition, connections between the dynamical properties of CAs (Lyapunov exponents and behavioral classes) and the performance of the identification algorithm are established and analyzed.}},
  author       = {{Bolt, Witold Tadeusz and Baetens, Jan and De Baets, Bernard}},
  issn         = {{2168-2267}},
  journal      = {{IEEE TRANSACTIONS ON CYBERNETICS}},
  keywords     = {{LYAPUNOV EXPONENTS,RULES,Table lookup,Genetic algorithms,Automata,Visualization,Cybernetics,Task analysis,Machine learning algorithms,Cellular automata (CAs),genetic algorithms (GAs),nonlinear dynamical systems,system identification}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{971--984}},
  title        = {{Identification of cellular automata based on incomplete observations with bounded time gaps}},
  url          = {{http://doi.org/10.1109/TCYB.2018.2875266}},
  volume       = {{50}},
  year         = {{2020}},
}
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