Document Type
Conference Proceeding
Publication Title
Late Breaking Papers of the 2001 Genetic and Evolutionary Computation Conference
Version
Author's Final Manuscript
Publication Date
2001
Abstract
We investigate the state change behavior of one-dimensional cellular automata during the solution of the binary density-classification task. Update rules of high, low and un- known fitness are applied to cellular au- tomata, thereby providing examples of high and low rates of successful classification. A spread factor, ω, is introduced and investi- gated as a numerical marker of state change behavior. The nature of ω describes complex or particle-like behavior on the part of the cellular automata over the middle region of initial configuration density-distribution, but breaks down at the ends. Because of the lim- itation on ω, a related jump-out term, jot, is selected for incorporation into the finess func- tion for genetic algorithm evolution of update rules. The inclusion of jot in the fitness func- tion significantly reduces the number of gen- erations required to reach high rates of suc- cessful classification (≥90%).
Citation
Ward, Em, Blank, Douglas S., Rolniak, Douglas, and Thompson, Dale R. (2001). Complexity as Fitness for Evolved Cellular Automata Update Rules. In Late Breaking Papers of the 2001 Genetic and Evolutionary Computation Conference.