An Artificial Ecosystem: Emergent Dynamics and Lifelike Properties

Rönkkö, Mauno

doi:10.1162/artl.2007.13.2.159

Cited by 19 publications

(6 citation statements)

References 22 publications

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“…Rö nkkö [49] has demonstrated how emergent lifelike properties can be simulated on the basis of the application of rules of interaction between information bearing particles ('atoms'). This modelling procedure is not constrained to any particular morphology, thus, in the case of multicellular organisms, where the constituent cellular phenotypes would be the information bearing particles, there would be no constraint on the body plans that could emerge: natural selection, however, would favour those best able to transduct energy from their specific ecosystem/environment.…”

Section: Discussionmentioning

confidence: 99%

Genes without prominence: a reappraisal of the foundations of biology

Annila

Baverstock

2014

J. R. Soc. Interface.

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The sequencing of the human genome raises two intriguing questions: why has the prediction of the inheritance of common diseases from the presence of abnormal alleles proved so unrewarding in most cases and how can some 25 000 genes generate such a rich complexity evident in the human phenotype? It is proposed that light can be shed on these questions by viewing evolution and organisms as natural processes contingent on the second law of thermodynamics, equivalent to the principle of least action in its original form. Consequently, natural selection acts on variation in any mechanism that consumes energy from the environment rather than on genetic variation. According to this tenet cellular phenotype, represented by a minimum free energy attractor state comprising active gene products, has a causal role in giving rise, by a self-similar process of cell-to-cell interaction, to morphology and functionality in organisms, which, in turn, by a self-similar process entailing Darwin's proportional numbers are influencing their ecosystems. Thus, genes are merely a means of specifying polypeptides: those that serve free energy consumption in a given surroundings contribute to cellular phenotype as determined by the phenotype. In such natural processes, everything depends on everything else, and phenotypes are emergent properties of their systems.

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Section: Discussionmentioning

confidence: 99%

Genes without prominence: a reappraisal of the foundations of biology

Annila

Baverstock

2014

J. R. Soc. Interface.

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“…Several researchers [8,21,14] claim that ecosystemic models are well suited to the generation of life-like behaviours, and perhaps even creativity. Further, an artificial system shown to pass Bedau et al's test for unbounded evolutionary activity had its success attributed to ecosystemic interactions [5].…”

Section: Artificial Life Modelsmentioning

confidence: 99%

Long-term evolutionary dynamics in heterogeneous cellular automata

Medernach

Kowaliw²,

Ryan

et al. 2013

Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation

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In this work we study open-ended evolution through the analysis of a new model, HetCA, for "heterogeneous cellular automata". Striving for simplicity, HetCA is based on classical two-dimensional CA, but differs from them in several key ways: cells include properties of "age", "decay", and "quiescence"; cells utilize a heterogeneous transition function, one inspired by genetic programming; and there exists a notion of genetic transfer between adjacent cells. The cumulative effect of these changes is the creation of an evolving ecosystem of competing cell colonies. To evaluate the results of our new model, we define a measure of phenotypic diversity on the space of cellular automata. Via this measure, we contrast HetCA to several controls known for their emergent behaviours-homogeneous CA and the Game of Life-and several variants of our model. This analysis demonstrates that HetCA has a capacity for long-term phenotypic dynamics not readily achieved in other models. Runs exceeding one million time steps do not exhibit stagnation or even cyclic behaviour. Further, we show that the design choices are well motivated, as the exclusion of any one of them disrupts the long-term dynamics.

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“…Artificial ecosystems are believed to be capable of supporting a rich array of emergent dynamics quite independent of evolutionary pressures. That is, in a simple particle-based environment using only static agent rules, the resulting dynamics alone are capable of generating complex patterns and life-like properties [31].…”

Section: Evoecomentioning

confidence: 99%

Promoting Creative Design in Interactive Evolutionary Computation

Kowaliw¹,

Dorin

McCormack

2012

IEEE Trans. Evol. Computat.

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Abstract-We use a new measure of creativity as a guide in an interactive evolutionary art task and tie the results to natural language usage of the term "creative". Following previous work, we explore a tractable definition of creativity, one emphasizing the novelty of systems, and its addition to an interactive application. We next introduce a generative ecosystemic art system, EvoEco, an agent-based pixel-level means of generating images. EvoEco is used as a component of an online survey which asks users to evolve a pleasing image and then rank the success of the process and its output. Evolutionary search is augmented with the creativity measure, and compared with control groups augmented with either random search or a measure of phenotypic distance. We show that users consistently rate the creativity measureenhanced version as more "creative" and "novel" than other search techniques. We further derive additional insights into appropriate forms of genetic representation and pattern spacetraversal in an interactive evolutionary algorithm.

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An Artificial Ecosystem: Emergent Dynamics and Lifelike Properties

Cited by 19 publications

References 22 publications

Genes without prominence: a reappraisal of the foundations of biology

Genes without prominence: a reappraisal of the foundations of biology

Long-term evolutionary dynamics in heterogeneous cellular automata

Promoting Creative Design in Interactive Evolutionary Computation

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