Degeneracy: A design principle for achieving robustness and evolvability

Whitacre, James M.; Bender, Axel

doi:10.1016/j.jtbi.2009.11.008

Cited by 172 publications

(187 citation statements)

References 31 publications

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“…But it is their capacity to evolve, learn and adapt that ultimately differentiates them from other complex systems: past experiences filter through, or influence, future states of the system due to a cumulative process (Deacon 2010). Like evolutionary (Whitacre and Bender 2010) and developmental (Edelman and Gally 2001) systems, language displays all the hallmarks of a CAS:…”

Section: The Three Complex Adaptive Systems Of Languagementioning

confidence: 99%

Integrating Cognitive Linguistics and language evolution research

Pleyer

Winters

2015

THS

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Abstract. In this paper we argue that we can gain important insights on the evolution of language and cognition by integrating evolutionary linguistics and the framework of Cognitive Linguistics. In Cognitive Linguistics, language is seen as tightly integrated with cognition as a whole. Construction Grammar and usage-based approaches are closely related to the Cognitive-Linguistic paradigm. Construction Grammar proposes that knowledge of language can be defined as the knowledge of form-meaning pairings of different degrees of schematicity and complexity, whereas usage-based approaches stress that language acquisition and processing are based on instances of actual language usage. As we demonstrate in this paper, concepts from Cognitive Linguistics, Construction Grammar, and usage-based approaches can help in elucidating the cognitive and interactional factors involved in language evolution. The paper will focus on two main areas: In evolutionary linguistics, language is seen as a complex adaptive system whose structure emerges out of the interaction of three other complex adaptive systems at three different timescales: ontogeny, glossogeny, and phylogeny. Cognitive Linguistics can help in specifying common cognitive factors and processes that play a role on all three of these timescales. Secondly, a Cognitive-Linguistic and constructionist, usage-based perspective can shed light on the cognitive factors underlying the origin of the division of labour between contentful ("lexical") and procedural ("grammatical") constructions in language structure. In a Cognitive-Linguistic perspective, this development can be related to the trade-off between the cognitive factors of learnability and expressivity.

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Section: The Three Complex Adaptive Systems Of Languagementioning

confidence: 99%

Integrating Cognitive Linguistics and language evolution research

Pleyer

Winters

2015

THS

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“…To elucidate the relationship between robustness and evolvability in natural systems, several theoretical models have been put forth (e.g., [15,16,17,18]). Central to many of these analyses is the concept of a genotype network (a.k.a.…”

Section: Introductionmentioning

confidence: 99%

Robustness, Evolvability, and Accessibility in Linear Genetic Programming

Payne

Banzhaf

et al. 2011

Lecture Notes in Computer Science

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Abstract. Whether neutrality has positive or negative effects on evolutionary search is a contentious topic, with reported experimental results supporting both sides of the debate. Most existing studies use performance statistics, e.g., success rate or search efficiency, to investigate if neutrality, either embedded or artificially added, can benefit an evolutionary algorithm. Here, we argue that understanding the influence of neutrality on evolutionary optimization requires an understanding of the interplay between robustness and evolvability at the genotypic and phenotypic scales. As a concrete example, we consider a simple linear genetic programming system that is amenable to exhaustive enumeration, and allows for the full characterization of these properties. We adopt statistical measurements from RNA systems to quantify robustness and evolvability at both genotypic and phenotypic levels. Using an ensemble of random walks, we demonstrate that the benefit of neutrality crucially depends upon its phenotypic distribution.

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“…2.4) of functional robustness, evolvability and adaptation (Albantakis et al, 2014;Edelman and Gally, 2001;Joshi et al, 2013;Kitano, 2007;Mukunda and Narayanan, 2017;Sarasso et al, 2015;Sporns et al, 2000;Stelling et al, 2004;Tononi et al, 1996Tononi et al, , 1999Wagner, 2005Wagner, , 2008Whitacre and Bender, 2010;Whitacre, 2010).…”

Section: Curse-of-dimensionality or Evolutionary Robustnessmentioning

confidence: 99%

“…http://dx.doi.org/10.1101/203943 doi: bioRxiv preprint first posted online Oct. 16, 2017; quantitative complexity measures and robustness with reference to several physiological and pathophysiological attributes (Albantakis et al, 2014;Edelman and Gally, 2001;Joshi et al, 2013;Kitano, 2007;Sarasso et al, 2015;Sporns et al, 2000;Stelling et al, 2004;Tononi et al, 1996Tononi et al, , 1999Wagner, 2005Wagner, , 2008Whitacre and Bender, 2010;Whitacre, 2010); and (c) plasticity models that have accounted for concomitant changes in multiple components (Secs. 3.6-3.7) rather than focusing on an one-toone relationship between functional plasticity and one specific component that undergoes changes Anirudhan and Narayanan, 2015;LeMasson et al, 1993;Mukunda and Narayanan, 2017;O'Leary et al, 2013;Siegel et al, 1994;Srikanth and Narayanan, 2015).…”

Section: Curse-of-dimensionality or Evolutionary Robustnessmentioning

confidence: 99%

Degeneracy in hippocampal physiology and plasticity

Rathour

Narayanan

2017

Preprint

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Degeneracy, defined as the ability of structurally disparate elements to perform analogous function, has largely been assessed from the perspective of maintaining robustness of physiology or plasticity. How does the framework of degeneracy assimilate into an encoding system where the ability to change is an essential ingredient for storing new incoming information? Could degeneracy maintain the balance between the apparently contradictory goals of the need to change for encoding and the need to resist change towards maintaining homeostasis? In this review, we explore these fundamental questions with the mammalian hippocampus as an example encoding system. We systematically catalog lines of evidence, spanning multiple scales of analysis, that demonstrate the expression of degeneracy in hippocampal physiology and plasticity. We assess the potential of degeneracy as a framework to achieve encoding and homeostasis without cross-interferences, and postulate that multiscale parametric and interactional complexity could establish disparate routes towards accomplishing these conjoint goals. These disparate routes then provide several degrees of freedom to the encodinghomeostasis system in accomplishing its tasks in an input-and state-dependent manner. Finally, the expression of degeneracy spanning multiple scales offers an ideal reconciliation to several outstanding controversies, through the recognition that the seemingly contradictory disparate observations are merely alternate routes that the system might recruit towards accomplishment of its goals. Juxtaposed against the ubiquitous prevalence of degeneracy and its strong links to evolution, it is perhaps apt to add a corollary to Theodosius Dobzhansky's famous quote and state "nothing in physiology makes sense except in the light of degeneracy".peer-reviewed)

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Degeneracy: A design principle for achieving robustness and evolvability

Cited by 172 publications

References 31 publications

Integrating Cognitive Linguistics and language evolution research

Integrating Cognitive Linguistics and language evolution research

Robustness, Evolvability, and Accessibility in Linear Genetic Programming

Degeneracy in hippocampal physiology and plasticity

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