A Vivisection of the ev Computer Organism: Identifying Sources of Active Information

Montanez, George D.; Ewert, Winston; Dembski, William A.; Marks, Robert J.

doi:10.5048/bio-c.2010.3

Cited by 10 publications

(4 citation statements)

References 22 publications

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“…Thus, the prescribed sequencing blossoms into deeper layers of meaning (Abel, 2000, 2011c, 2012a,b; Kellera, 2011; D'Onofrio et al, 2012). In molecular biological messages, “meaning” translates into successful “biofunction” (Huttegger, 2007; Kauffman, 2007; Kolen and Van de Vijver, 2007; Livaditis and Tsatalmpasidou, 2007; Sherman and Deacon, 2007; Abel, 2009c; Marsen, 2009; Alp, 2010; Bedau, 2010; Benner, 2010; Levy, 2010; Montañez et al, 2010; Tirard et al, 2010). …”

Section: Resultsmentioning

confidence: 99%

Redundancy of the genetic code enables translational pausing

D'Onofrio

Abel²

2014

Front. Genet.

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The codon redundancy (“degeneracy”) found in protein-coding regions of mRNA also prescribes Translational Pausing (TP). When coupled with the appropriate interpreters, multiple meanings and functions are programmed into the same sequence of configurable switch-settings. This additional layer of Ontological Prescriptive Information (PIo) purposely slows or speeds up the translation-decoding process within the ribosome. Variable translation rates help prescribe functional folding of the nascent protein. Redundancy of the codon to amino acid mapping, therefore, is anything but superfluous or degenerate. Redundancy programming allows for simultaneous dual prescriptions of TP and amino acid assignments without cross-talk. This allows both functions to be coincident and realizable. We will demonstrate that the TP schema is a bona fide rule-based code, conforming to logical code-like properties. Second, we will demonstrate that this TP code is programmed into the supposedly degenerate redundancy of the codon table. We will show that algorithmic processes play a dominant role in the realization of this multi-dimensional code.

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Section: Resultsmentioning

confidence: 99%

Redundancy of the genetic code enables translational pausing

D'Onofrio

Abel²

2014

Front. Genet.

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“…The concept of active information does not specify a source for the information, or even how the information is stored, it only measures its effects. 5 Active information is typically used to measure the amount of information present in various algorithms, such as in Ewert, Dembski, and Marks II (2009) and Montañez et al (2010), but it has also been used in measuring the degree of fine tuning in cosmology (Díaz-Pachón, Hössjer, and Marks II 2021) and judging the effectiveness of machine learning models (Bartlett and Holloway 2019). The fact that it is being designated as "information" does not mean that it is stored in an explicit digital format (it would be difficult to even conceptualize a "digital format" for cosmological fine-tuning, for instance), but merely that it can be reasoned about using information theory.…”

Section: Measuring Teleological Causationmentioning

confidence: 99%

Causal Capabilities of Teleology and Teleonomy in Life and Evolution

Bartlett

2023

OrgF

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Teleological causes have been generally disfavored in biological explanations because they have been thought to lack rigor or act as stand-ins for non-teleological processes which are simply not yet understood sufficiently. Teleological explanations in biology have been limited to only teleonomic causes, which are teleological causes that are due to codes or similarly reified mechanisms. However, advances in the conceptualization of teleological and teleonomic causation have allowed for more quantitative analyses of both. Additionally, although teleonomy has been historically excluded from potential causes of evolution, new research has shown that teleonomy actually plays a significant role in evolution. Combining these advances with advances in computability theory and information theory have allowed for a more rigorous and quantitative analysis of the capabilities and limitations of teleonomy in evolution.

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“…Other programs have claimed to simulate Darwinian evolution. These incluvde AVIDA [11,23] and ev [12,33]. Like AVIDA and ev, metabiology makes use of external information sources to assist in the search.…”

Section: Metabiology Landscapesmentioning

confidence: 99%

Active Information in Metabiology

Ewert¹,

Dembski²,

Marks³

2013

BIO-Complexity

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Metabiology is a fascinating intellectual romp in the surreal world of the mathematics of algorithmic information theory. In this world, halting oracles hunt for busy beaver numbers and busy beaver numbers unearth Chaitin's number, knowledge of which in turn allows resolution of numerous unsolved mathematical problems, many of whose solutions would earn large cash bounties. All this, despite the fact that halting oracles can't be implemented on a computer, a computer can never make a list of busy beaver numbers, and Chaitin's number, always a positive real number less than one, is proven to be unknowable. The fun of metabiology is the application of these ideas to illustrate Darwinian evolution. When metabiology's evolutionary process is stripped of the glitter of algorithmic information theory, however, what remains is a procedure similar to that used in other attempts to model Darwinian evolution, like the ev and AVIDA computer programs. Metabiology, like ev and AVIDA, succeeds because available sources of knowledge about the solution being sought can be mined. We show the mining of information from a halting oracle has striking similarities to mining information from a simple Hamming oracle. Unlike a halting oracle, however, Hamming oracles can be implemented on a computer. We demonstrate that for both oracles, information can be mined by search strategies that are analogous in some respects even though the methods differ; in both cases the search strategy used greatly influences the result. Because metabiology's process relies on unknowable numbers and infinite resources, its reported relative performance measures can only be expressed asymptotically. That is, the results of metabiology are only proven to be true on the largest possible scale. In fact, simple simulations using bounded resources suggest the asymptote is not always approached quickly, indicating that metabiology results may only hold for scales larger than any practical system.

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A Vivisection of the ev Computer Organism: Identifying Sources of Active Information

Cited by 10 publications

References 22 publications

Redundancy of the genetic code enables translational pausing

Redundancy of the genetic code enables translational pausing

Causal Capabilities of Teleology and Teleonomy in Life and Evolution

Active Information in Metabiology

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