Title :
Extracting Boolean rules from CA patterns
Author :
Yang, Yingxu ; Billings, S.A.
Author_Institution :
Sheffield Univ., UK
fDate :
8/1/2000 12:00:00 AM
Abstract :
A multiobjective genetic algorithm (GA) is introduced to identify both the neighborhood and the rule set in the form of a parsimonious Boolean expression for both one- and two-dimensional cellular automata (CA). Simulation results illustrate that the new algorithm performs well even when the patterns are corrupted by static and dynamic noise
Keywords :
Boolean functions; cellular automata; genetic algorithms; Boolean rules extraction; cellular automata; dynamic noise; multiobjective genetic algorithm; rule set; simulation results; static noise; Automata; Concurrent computing; Digital circuits; Genetic algorithms; Hardware; Inverse problems; Mathematical model; Modeling; Parallel algorithms; Systems engineering and theory;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.865174
