Shrinking the Genotype: L-systems for EHW?

Haddow, Pauline C.; Tufte, Gunnar; Remortel, Piet van

doi:10.1007/3-540-45443-8_11

Cited by 59 publications

(32 citation statements)

References 10 publications

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“…L-Systems model plant development using a set of rules via a grammar implementation, thus aiming to imitate biological development of plants using recursive functions. L-Systems have been applied to circuit design problems [32], [49], neural networks [50], and 3-D morphology design [51], [52]. Another example of a grammatical developmental system is cellular encoding (CE) [53].…”

Section: B Models Of Artificial Developmentmentioning

confidence: 99%

An Investigation of the Importance of Mechanisms and Parameters in a Multicellular Developmental System

Kuyucu

Trefzer

Miller

et al. 2011

IEEE Trans. Evol. Computat.

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Abstract-Multicellular organisms in biology possess invaluable characteristics, which artificial systems in engineering lack, such as adaptivity and robustness. Modeling biologically inspired multicellular developmental systems in evolutionary computation have been considered for a number of years, and there exist many developmental simulations that capture multicellular characteristics of biological organisms. However, the relative importance of many mechanisms in such models is still poorly understood. This paper undertakes a detailed investigation of the importance of many mechanisms and parameters on the organizational behavior of a gene regulatory network based artificial developmental system via classical pattern matching experiments. The work leads to an improved understanding of artificial multicellular development, which will assist in its utilization in the application of evolutionary computation. It may also provide a better understanding of mechanisms of biological development.

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Section: B Models Of Artificial Developmentmentioning

confidence: 99%

An Investigation of the Importance of Mechanisms and Parameters in a Multicellular Developmental System

Kuyucu

Trefzer

Miller

et al. 2011

IEEE Trans. Evol. Computat.

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“…The cell program can even be a neural network [19] or an interpreted programming language [30], although these last two systems were only applied to the development of neural networks in software. Since simulating gene regulatory networks or cell programs may be computationally intensive, more abstract developmental systems such as L-Systems can be used [31,82]. Developmental systems can also provide fault-tolerance in electronics by letting the circuit develop on spare cells in case of faults as in Embryonics [56,57] or by letting the developmental system repair or grow new cells [47,53,54,59].…”

Section: Developmental Systemsmentioning

confidence: 99%

Evolutionary morphogenesis for multi-cellular systems

Roggen

Federici

Floreano

2006

Genet Program Evolvable Mach

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With a gene required for each phenotypic trait, direct genetic encodings may show poor scalability to increasing phenotype length. Developmental systems may alleviate this problem by providing more efficient indirect genotype to phenotype mappings. A novel classification of multi-cellular developmental systems in evolvable hardware is introduced. It shows a category of developmental systems that up to now has rarely been explored. We argue that this category is where most of the benefits of developmental systems lie (e.g. speed, scalability, robustness, inter-cellular and environmental interactions that allow fault-tolerance or adaptivity). This article describes a very simple genetic encoding and developmental system designed for multi-cellular circuits that belongs to this category. We refer to it as the morphogenetic system. The morphogenetic system is inspired by gene expression and cellular differentiation. It focuses on low computational requirements which allows fast execution and a compact hardware implementation. The morphogenetic system shows better scalability compared to a direct genetic encoding in the evolution of structures of differentiated cells, and its dynamics provides fault-tolerance up to high fault rates. It outperforms a direct genetic encoding when evolving spiking neural networks for

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“…The morphogenetic system is inspired by the mechanisms of gene expression and cell differentiation of living organism [2], notably by the fact that concentrations of proteins and inter-cellular chemical signalling regulate the functionality of cells. Other works related to this morphogenetic systems include L-Systems [7], use of developmental processes [3,6], and also approximate representations [1] seeking to compress the genotype.…”

Section: Morphogenetic Codingmentioning

confidence: 99%

A Morphogenetic Evolutionary System: Phylogenesis of the POEtic Circuit

Roggen

Floreano

Mattiussi

2003

Evolvable Systems: From Biology to Hardware

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Abstract. This paper describes a new evolutionary mechanism developed specifically for cellular circuits. Called morphogenetic system, it is inspired by the mechanisms of gene expression and cell differentiation found in living organisms. It will be used as the phylogenetic (evolutionary) mechanism in the POEtic project. The POEtic project will deliver an electronic circuit, called the POEtic circuit, with the capability to evolve (Phylogenesis), self-repair and grow (Ontogenesis) and learn (Epigenesis). The morphogenetic system is applied to the generation of patterns and to the evolution of spiking neural networks, with experiments of pattern recognition and obstacle avoidance with robots. Experimental results show that the morphogenetic system outperforms a direct genetic coding in several experiments.

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Shrinking the Genotype: L-systems for EHW?

Cited by 59 publications

References 10 publications

An Investigation of the Importance of Mechanisms and Parameters in a Multicellular Developmental System

An Investigation of the Importance of Mechanisms and Parameters in a Multicellular Developmental System

Evolutionary morphogenesis for multi-cellular systems

A Morphogenetic Evolutionary System: Phylogenesis of the POEtic Circuit

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