Phylogeny, ontogeny, and epigenesis: Three sources of biological inspiration for softening hardware

Sánchez, Eduardo García; Mange, Daniel; Sipper, Moshe; Tomassini, Marco; Pérez-Uribe, Andrés; Stauffer, André

doi:10.1007/3-540-63173-9_37

Cited by 37 publications

(26 citation statements)

References 31 publications

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“…We also take the view of Sanchez et al [13] in seeing a distinction between replication and reproduction. Specifically, replication seeks to copy an entire system without error, while reproduction allows for variations.…”

Section: Overview and Historymentioning

confidence: 99%

A Universal Framework for Analysis of Self-Replication Phenomena

Adams

Lipson

2009

Entropy

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In this paper, we propose definitions for a general, domain-independent concept of replicability and specifically focus on the notion of self-replication. We argue that selfreplication should not be viewed as a binary property of a system, but rather as a continuously valued property of the interaction between a system and its environment. This property, selfreplicability, represents the effect of the presence of a system upon the future presence of similar systems. We demonstrate both analytical and computational analysis of self-replicability for four distinct systems involving both discrete and continuous, formal and physical behaviors.

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Section: Overview and Historymentioning

confidence: 99%

A Universal Framework for Analysis of Self-Replication Phenomena

Adams

Lipson

2009

Entropy

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“…Bio-inspiration in the design of digital hardware finds its source in essentially three biological models [9,10]: Phylogenesis (P), the history of the evolution of the species through time, Ontogenesis (O), the development of an individual as directed by his genetic code, from its first cell to the full organism, and Epigenesis (E), the development of an individual through learning processes. All of these models, to a greater or lesser extent have been used as a source of inspiration for the development of computing machines (such as the ontogenesis in the Embryonics project or epigenesis for artificial neural networks) but before the POEtic project [1,2], no hardware substrate had been developed that could combine the three axes of bio-inspiration into one single circuit.…”

Section: The Poetic Tissuementioning

confidence: 99%

MOVE Processors That Self-replicate and Differentiate

Rossier

Thoma

Mudry

et al. 2006

Biologically Inspired Approaches to Advanced Information Technology

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Abstract. This article describes an implementation of a basic multiprocessor system that exhibits replication and differentiation abilities on the POEtic tissue, a programmable hardware designed for bio-inspired applications [1,2] . As for a living organism, whose existence starts with only one cell that first divides, our system begins with only one totipotent processor, able to implement any of the cells required by the final organism, which can also fully replicate itself, using the functionalities of the POEtic substrate. Then, analogously to the cells in a developing organism, our just replicated totipotent processors differentiate in order to execute their specific part of the complete organism functionality. In particular, we will present a working realization using MOVE processors whose instructions define the flow of data rather than the operations to be executed [3]. It starts with one basic MOVE processor that first replicates itself three times; the four resulting processors then differentiate and connect together to implement a multi-processor modulus-60 counter.

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“…This model has been introduced by researcher E. Sanchez in reference [7]. Upon the POE-based model has been built up four hierarchical levels of organization [8].…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional artificial organism model developed upon a two-layer coarse-fine-grid network approach

Szász

2017

IRASE

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In an attempt to devise a model which more closely imitates cellular biology a three-dimensional (3D) artifi cial organism model developed upon a two-layer coarse-fi ne-grid network model is proposed in this paper. The strength of this original approach is that it endeavors to capture the complexity of both the cellular networks as well as that of the biological cell itself, by implementing the internal biological phenomena of an organism into a 3D two different network topology hardware layer. In essence, this model not only keeps the full advantages of previously created 2D models that enable the implementation of similar self-replicating or selfrepairing abilities akin to those expressed by its cellular equivalents in nature, but there the inherent need of artifi cial cell structures to fulfi ll the entire role of a biological cell in the network is also expressed. Computer-aided simulation results prove that this kind of 3D coarse-fi ne-grid approach is well feasible physically therefore the model has been implemented into a computing platform made of custom reconfi gurable Field Programmable Gate Array (FPGA) processors.

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Phylogeny, ontogeny, and epigenesis: Three sources of biological inspiration for softening hardware

Cited by 37 publications

References 31 publications

A Universal Framework for Analysis of Self-Replication Phenomena

A Universal Framework for Analysis of Self-Replication Phenomena

MOVE Processors That Self-replicate and Differentiate

Three-dimensional artificial organism model developed upon a two-layer coarse-fine-grid network approach

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