Evolving Cellular Automata

Čeněk, Martin; Mitchell, Melanie

doi:10.1007/978-0-387-30440-3_191

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…После фон Неймана исследования были продолжены его учеником Станиславом Уламом и Джоном Холландом -сотрудниками университета Лос-Аламос в университете Мичигана [8][9][10].…”

Section: анализ литературных данных и постановка проблемыunclassified

Peculiarities of hardware implementation of generalized cellular tetra automaton

Аноприенко

Федоров

Иваница

et al. 2015

TAPR

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Section: анализ литературных данных и постановка проблемыunclassified

Peculiarities of hardware implementation of generalized cellular tetra automaton

Аноприенко

Федоров

Иваница

et al. 2015

TAPR

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“…the states of its neighboring cells) according to pre-defined rules. In a neural cellular automata, instead of having hand-designed rules, a neural network learns the update rules [5,32,36]. In a recent impressive demonstration of a neural CA, Mordvintsev et al trained a neural CA to grow complex two-dimensional images starting from a few initial cells [33].…”

Section: Introductionmentioning

confidence: 99%

Regenerating Soft Robots through Neural Cellular Automata

Horibe

Walker

Risi

2021

Preprint

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Morphological regeneration is an important feature that highlights the environmental adaptive capacity of biological systems. Lack of this regenerative capacity significantly limits the resilience of machines and the environments they can operate in. To aid in addressing this gap, we develop an approach for simulated soft robots to regrow parts of their morphology when being damaged. Although numerical simulations using soft robots have played an important role in their design, evolving soft robots with regenerative capabilities have so far received comparable little attention. Here we propose a model for soft robots that regenerate through a neural cellular automata. Importantly, this approach only relies on local cell information to regrow damaged components, opening interesting possibilities for physical regenerable soft robots in the future. Our approach allows simulated soft robots that are damaged to partially regenerate their original morphology through local cell interactions alone and regain some of their ability to locomote. These results take a step towards equipping artificial systems with regenerative capacities and could potentially allow for more robust operations in a variety of situations and environments. The code for the experiments in this paper is available at: github.com/KazuyaHoribe/RegeneratingSoftRobots.

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Shift-symmetric configurations in two-dimensional cellular automata: Irreversibility, insolvability, and enumeration

Banda

Caughman

Čeněk

et al. 2019

Chaos: An Interdisciplinary Journal of Nonlinear Science

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The search for symmetry as an unusual yet profoundly appealing phenomenon, and the origin of regular, repeating configuration patterns have been for a long time a central focus of complexity science, and physics.Here, we introduce group-theoretic concepts to identify and enumerate the symmetric inputs, which result in irreversible system behaviors with undesired effects on many computational tasks. The concept of so-called configuration shift-symmetry is applied on two-dimensional cellular automata as an ideal model of computation. The results show the universal insolvability of "nonsymmetric" tasks regardless of the transition function. By using a compact enumeration formula and bounding the number of shift-symmetric configurations for a given lattice size, we efficiently calculate how likely a configuration randomly generated from a uniform or density-uniform distribution turns shift-symmetric. Further, we devise an algorithm detecting the presence of shift-symmetry in a configuration.The enumeration and probability formulas can directly help to lower the minimal expected error for many crucial (non-symmetric) distributed problems, such as leader election, edge detection, pattern recognition, convex hull/minimum bounding rectangle, and encryption. Besides cellular automata, the shift-symmetry analysis can be used to study the non-linear behavior in various synchronous rule-based systems that include inference engines, Boolean networks, neural networks, and systolic arrays. not completely known. To understand the role of symmetry of the starting configurations (the inputs), how they are processed (the machine), and produce the final configurations with desired properties (the outputs) we use a cellular automata (CA) as a simple distributed model of computation. First introduced by John von Neumman, CAs allowed to explore logical requirements for machine self-replication and information processing in nature [38]. Despite having no central control and limited communication among the components, CAs are capable of universal computation and can exhibit various dynamical regimes [8,38,46,52]. As one of the structurally simplest distributed systems, CAs have become a fundamental model for studying complexity in its purist form [16,53]. Subsequently, CAs have been successfully employed in numerous research fields and applications, such as modeling artificial life [29], physical equations [19,47], and social and biological simulations [18,25,42,43].

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Evolving Cellular Automata

Cited by 4 publications

References 31 publications

Peculiarities of hardware implementation of generalized cellular tetra automaton

Peculiarities of hardware implementation of generalized cellular tetra automaton

Regenerating Soft Robots through Neural Cellular Automata

Shift-symmetric configurations in two-dimensional cellular automata: Irreversibility, insolvability, and enumeration

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