Developmental Effects on Tuneable Fitness Landscapes

Remortel, Piet van; Ceuppens, Johan; Defaweux, Anne; Lenaerts, Tom; Manderick, Bernard

doi:10.1007/3-540-36553-2_11

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…A number of EH research groups are involved in developmental approaches to EH [20,59,[67][68][69][70][71][72][73], including theoretical and practical investigations into the feasibility of development as an EH technique [74][75][76][77]. However, there is much research to be conducted before such a technique can be said to really be moving along the path towards an efficient technique for EH.…”

Section: Development and Modularisationmentioning

confidence: 99%

Challenges of evolvable hardware: past, present and the path to a promising future

Haddow

Tyrrell

2011

Genet Program Evolvable Mach

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Nature is phenomenal. The achievements in, for example, evolution are everywhere to be seen: complexity, resilience, inventive solutions and beauty. Evolvable Hardware (EH) is a field of evolutionary computation (EC) that focuses on the embodiment of evolution in a physical media. If EH could achieve even a small step in natural evolution's achievements, it would be a significant step for hardware designers. Before the field of EH began, EC had already shown artificial evolution to be a highly competitive problem solver. EH thus started off as a new and exciting field with much promise. It seemed only a matter of time before researchers would find ways to convert such techniques into hardware problem solvers and further refine the techniques to achieve systems that were competitive with or better than human designs. However, 15 years on-it appears that problems solved by EH are only of the size and complexity of that achievable in EC 15 years ago and seldom compete with traditional designs. A critical review of the field is presented. Whilst highlighting some of the successes, it also considers why the field is far from reaching these goals. The paper further redefines the field and speculates where the field should go in the next 10 years.

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Section: Development and Modularisationmentioning

confidence: 99%

Challenges of evolvable hardware: past, present and the path to a promising future

Haddow

Tyrrell

2011

Genet Program Evolvable Mach

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“…Depending on the combination of environmental stimulus present cells may follow different ontogenetic pathways, see Figure 3 by a high degree of epistatic interactions at the genotypic level [4]. In addition GRN based models can suffer from effects such as pleiotropy and polygeny [5].…”

Section: Environmental Stimulusmentioning

confidence: 99%

Evolving plastic responses in artificial cell models

Maher

Morgan

Aodha

2009

2009 IEEE Congress on Evolutionary Computation

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Two variants of biologically inspired cell model, namely eukaryotic (containing a nucleus) and prokaryotic (without a nucleus) are compared in this research. The comparison investigates their relative evolvability and ability to integrate external environmental stimulus to direct protein pattern formation within a single cell. To the authors' knowledge there has been no reported work comparing the relative performance of eukaryotic and prokaryotic artificial cells models. We propose a novel system of protein translocation for eukaryotic cells based on the process of nucleocytoplasmic transport observed in biological cells. Results demonstrate that eukaryotic cell models exhibit a higher degree of sensitivity to environmental variations compared with prokaryotes. Based on these results we conclude that the process of transporting proteins to and from the nucleus plays a key role in shaping eukaryotic cell plasticity.

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“…These systems seek to solve the problem of scale by replacing the linear genotype-phenotype mapping, with a non-linear mapping. However, developmental mappings have a low degree of evolvability caused by high degrees of epistatic interactions at the genotypic level (Van Remortel et al, 2003). Enhancing the ability of the genome to allow for heterochronic mutations increases the number of successful genotypes (Stanley and Miikkulainen, 2003) by offering a variety of paths to each successful phenotype.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Cell Type on Artificial Development

Maher

Morgan

O’Riordan

et al. 2013

Advances in Artificial Life, ECAL 2013

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Two variants of biologically inspired cell model, namely eukaryotic (containing a nucleus) and prokaryotic(without a nucleus) are compared in this research. Experiments are designed to provide an understanding of how the evolved regulation of protein transport to and from the nucleus of the eukaryotic type cell gives rise to complex temporal dynamics that are not achievable in a prokaryoticcell. A novel system of protein movement based on the process of nucleocytoplasmic transport observed in the biological eukaryotic cell is proposed. Nucleocytoplasmic transport is considered by biologists to be one of the most important factors when determining the developmental trajectory of a cell, as it allows for additional control of transcription factors entering the nucleus, thereby regulating gene activity. Experiments contrast the ability of both cell models to generate protein patterns within the cytoplasm. Results demonstrate that the additional cell complexity of the eukaryotic does not impede the Gene Regulatory Networks control. For increasingly difficult tasks requiring precise temporal control the performance of the eukaryotic cell model outperforms the prokaryoticcell model. In addition, results demonstrate that the second level of regulation introduced by the transport process within the eukaryotic cell allows very precise control of gene activity and provides the EA with a source of heterochronic control not possible in prokaryotictype cells.

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Developmental Effects on Tuneable Fitness Landscapes

Cited by 5 publications

References 5 publications

Challenges of evolvable hardware: past, present and the path to a promising future

Challenges of evolvable hardware: past, present and the path to a promising future

Evolving plastic responses in artificial cell models

The Influence of Cell Type on Artificial Development

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