Evolution of biological complexity

Adami, Christoph; Ofria, Charles; Collier, Travis C.

doi:10.1073/pnas.97.9.4463

Cited by 489 publications

(388 citation statements)

References 21 publications

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“…Interestingly, Adami's experiments on digital organisms revealed a steady trend toward increased physical complexity in their evolution within a fixed environment (16). According to his theory and simulation data, evolution increases the amount of 'knowledge' an organism (or a population of organisms) accumulates about its niche.…”

Section: Physical Complexitymentioning

confidence: 99%

“…By contrast, KolmogorovChaitin complexity measures regularity/randomness within a sequence and therefore fails to address its meaning in the environment. a Information is a relative quantity -always about something, in case of the genome it is about the niche that an organism lives in (16,17). The theory of physical complexity uses two central concepts of Shannon's theory of information: entropy and information.…”

Section: Physical Complexitymentioning

confidence: 99%

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Physical Complexity and Cognitive Evolution

Jedlicka

2007

Worldviews, Science and Us

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Our intuition tells us that there is a general trend in the evolution of nature, a trend towards greater complexity. However, there are several definitions of complexity and hence it is difficult to argue for or against the validity of this intuition. Christoph Adami has recently introduced a novel measure called physical complexity that assigns low complexity to both ordered and random systems and high complexity to those in between. Physical complexity measures the amount of information that an organism stores in its genome about the environment in which it evolves. The theory of physical complexity predicts that evolution increases the amount of 'knowledge' an organism accumulates about its niche. It might be fruitful to generalize Adami's concept of complexity to the entire evolution (including the evolution of man). Physical complexity fits nicely into the philosophical framework of cognitive biology which considers biological evolution as a progressing process of accumulation of knowledge (as a gradual increase of epistemic complexity). According to this paradigm, evolution is a cognitive 'ratchet' that pushes the organisms unidirectionally towards higher complexity. Dynamic environment continually creates problems to be solved. To survive in the environment means to solve the problem, and the solution is an embodied knowledge. Cognitive biology (as well as the theory of physical complexity) uses the concepts of information and entropy and views the evolution from both the information-theoretical and thermodynamical perspective. Concerning humans as conscious beings, it seems necessary to postulate an emergence of a new kind of knowledge -a self-aware and self-referential knowledge. Appearence of selfreflection in evolution indicates that the human brain reached a new qualitative level in the epistemic complexity.

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Section: Physical Complexitymentioning

confidence: 99%

Section: Physical Complexitymentioning

confidence: 99%

Physical Complexity and Cognitive Evolution

Jedlicka

2007

Worldviews, Science and Us

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“…Genomic insight has made clear that protein diversity and biological function cannot be explained using just gene expression (Adami et al, 2000). Biological function will ultimately be determined by protein expression levels, in combination with each protein's structure, location and its interactions with other proteins and the environment.…”

Section: Tandem Mass Spectrometry: a Historical Perspectivementioning

confidence: 99%

Evolutionary Proteomics: Empowering Tandem Mass Spectrometry and Bioinformatics Tools for the Study of Evolution

Vega¹,

Rittschof²,

Dickinson³

et al. 2012

Tandem Mass Spectrometry - Applications and Principles

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“…Adami [5] proposed measuring evolution in artificial systems in terms of the complexity of an agent. In some ALife models, e.g.…”

Section: Measuring Evolutionmentioning

confidence: 99%

Measuring the Dynamics of Artificial Evolution

Burtsev

2003

Advances in Artificial Life

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Abstract. This paper presents results of measuring evolution in a simple ALife system. Interpretation of these results is based on the notion of dynamical systems. This approach enables the discovery of periods of high evolutionary activity, which can be treated as evolutionary transitions. Attempts were also made to locate possible cycles of trajectory in the genome phase space, and it was concluded that there were no such cycles. These results demonstrate the usefulness of a dynamical systems approach in analyzing the dynamics of artificial evolution and provide suggestions for further development.

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Evolution of biological complexity

Cited by 489 publications

References 21 publications

Physical Complexity and Cognitive Evolution

Physical Complexity and Cognitive Evolution

Evolutionary Proteomics: Empowering Tandem Mass Spectrometry and Bioinformatics Tools for the Study of Evolution

Measuring the Dynamics of Artificial Evolution

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