Searching for complex CA rules with GAs

Bilotta, Eleonora; Lafusa, Antonio; Pantano, Pietro

doi:10.1002/cplx.10063

Cited by 21 publications

(8 citation statements)

References 13 publications

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“…In an earlier work [20], we used a genetic algorithm based on input-entropy, to find complex rules of class IV for 1D CA [4]. In the 2D case, with the increase of k ϭ ͉S͉ and of r, the exhaustive rule becomes nontreatable, and it is necessary to utilize a more simple form to be used as genome to start the evolutionary process.…”

Section: Formal Aspects Of Cellular Automatamentioning

confidence: 99%

Life‐like self‐reproducers

2003

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In order to understand the interplay among information, genetic instructions, and phenotypic variations, self-reproducers discovered in two-dimensional cellular automata are considered as proto-organisms, which undergo to mutations as they were in a real environmental situation. We realized a computational model through which we have been able to discover the genetic map of the self-reproducers and the networks they use. Identifying in these maps sets of different functional genes, we found that mutations in the genetic sequences could affect both external shapes and behavior of the self-reproducers, thus realizing different life-like strategies in the evolution process. The results highlight that some strategies evolution uses in selecting organisms

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Section: Formal Aspects Of Cellular Automatamentioning

confidence: 99%

Life‐like self‐reproducers

2003

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“…Genetic algorithms have been used to address this problem by searching for particular behaviors in potentially complex rule spaces [10 -12]. The results of Bilotta et al [10] have shown that complex rule sets may actually have multiple values, which are the proportionality range of nondestructive rules. The behavior exhibited by multiple values explains the evolutive attractors as the cellular automata mature.…”

Section: Approachmentioning

confidence: 99%

Emergent behavior in two complex cellular automata rule sets

2005

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“…This is one of the most important open questions in current Complexity Science [Bilotta et al, 2003a[Bilotta et al, , 2003b.…”

Section: Representing Parameter Spacementioning

confidence: 99%

A Gallery of Chua Attractors: Part Iii

Bilotta

STRANGES

Pantano

2007

Int. J. Bifurcation Chaos

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The visualization of patterns related to chaos is a challenge for those who are part of today's dynamical systems community, especially when we consider the aim of providing users with the ability to visually analyze and explore large, complex datasets related to chaos. Thus visualization could be considered a useful element in the discovery of unexpected relationships and dependencies that may exist inside the domain of chaos, both in the phase and the parameter spaces. In the second part of "A Gallery of Chua attractors", we presented an overview of forms which can only be produced by the physical circuit. In Part III, we illustrate the variety and beauty of the strange attractors produced by the dimensionless version of the system. As in our earlier work, we have used ad hoc methods, such as bifurcation maps and software tools, allowing rapid exploration of parameter space. Applying these techniques, we show how it is possible, starting from attractors described in the literature, to find new families of patterns, with a special focus on the cognitive side of information seeking and on qualitative processes of change in chaos, thus demonstrating that traditional categories of chaos exploration need to be renewed.After a brief introduction to dimensionless equations for Chua's oscillator, we show 150 attractors, which we represent using three-dimensional images, time series and FFT diagrams. For the most important patterns, we also report Lyapunov exponents. To show the position of dimensionless attractors in parameter space, we use parallel coordinate techniques that facilitate the visualization of high dimensional spaces. We use Principal Components Analysis (PCA) and Mahalanobis Distance to provide additional tools for the exploration and visualization of the structure of the parameter space.

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Searching for complex CA rules with GAs

Abstract: An important problem in the theory of cellular automata (CA) is the research of complex rules

Cited by 21 publications

References 13 publications

Life‐like self‐reproducers

Life‐like self‐reproducers

Emergent behavior in two complex cellular automata rule sets

A Gallery of Chua Attractors: Part Iii

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