Developmental processes in silicon: an engineering perspective

Tempesti, Gianluca; Mange, Daniel; Petraglio, Enrico; Stauffer, André; Thoma, Yann

doi:10.1109/eh.2003.1217677

Cited by 13 publications

(13 citation statements)

References 38 publications

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“…On the other hand there are developmental systems which may be inspired by biology, but do not seek biological plausibility. This second approach is a more pragmatic view of development [78].…”

Section: Resultsmentioning

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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Section: Resultsmentioning

confidence: 99%

Evolutionary morphogenesis for multi-cellular systems

Roggen

Federici

Floreano

2006

Genet Program Evolvable Mach

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“…5 Although more biologically inspired, a micro-model developmental system does not necessarily model biological development perfectly. In fact there is much work in this type of artificial development with diverse design constraints, those that model biology closely [1], [13], [54]- [56], those that aim to model biological development in a simplistic fashion [19], [57], [58], and models that are "in-between" [3], [4], [9], [31], [59]. Mimicking biology closely should provide a developmental system with high evolvability [30], [60], whereas a simplistic model would reduce the number of complicated processes that exist in biological development, reducing simulation times drastically.…”

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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“…However, mimicking biology closely in the implementation of a developmental system can over-complicate the developmental system and render it practically unusable for Evolutionary Computation (EC) applications. Thus it may be more practical to have a simple developmental mechanism that is rather engineered for EC than copied from biology [12], [18].…”

Section: Development In Evolvable Hardwarementioning

confidence: 99%

A scalable solution to n-bit parity via artificial development

Kuyucu

Trefzer

Miller

et al. 2009

2009 Ph.D. Research in Microelectronics and Electronics

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Abstract-The design of electronic circuits with model-free heuristics like evolutionary algorithms is an attractive concept and field of research. Although successful to a point, evolution of circuits that are bigger than a 3-bit multiplier is hindered by the scalability problem. Modelling the biological development as an artificial genotype-phenotype mapping mechanism has been shown to improve scalability on some simple circuit problems and pattern formations. As a candidate solution to the scalability issue, an artificial developmental system is presented.The presented artificial developmental system is shown to develop a scalable parity circuit, which could be infinitely developed to build a growing parity circuit, hence, represents a general, scalable solution to n-bit parity.The result obtained further supports the artificial developmental system as a good candidate solution to the scalability problem in evolvable hardware.

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Developmental processes in silicon: an engineering perspective

Cited by 13 publications

References 38 publications

Evolutionary morphogenesis for multi-cellular systems

Evolutionary morphogenesis for multi-cellular systems

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

A scalable solution to n-bit parity via artificial development

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