Literature DB >> 25515264

Mapping an expanding territory: computer simulations in evolutionary biology.

Philippe Huneman1.   

Abstract

The pervasive use of computer simulations in the sciences brings novel epistemological issues discussed in the philosophy of science literature since about a decade. Evolutionary biology strongly relies on such simulations, and in relation to it there exists a research program (Artificial Life) that mainly studies simulations themselves. This paper addresses the specificity of computer simulations in evolutionary biology, in the context (described in Sect. 1) of a set of questions about their scope as explanations, the nature of validation processes and the relation between simulations and true experiments or mathematical models. After making distinctions, especially between a weak use where simulations test hypotheses about the world, and a strong use where they allow one to explore sets of evolutionary dynamics not necessarily extant in our world, I argue in Sect. 2 that (weak) simulations are likely to represent in virtue of the fact that they instantiate specific features of causal processes that may be isomorphic to features of some causal processes in the world, though the latter are always intertwined with a myriad of different processes and hence unlikely to be directly manipulated and studied. I therefore argue that these simulations are merely able to provide candidate explanations for real patterns. Section 3 ends up by placing strong and weak simulations in Levins' triangle, that conceives of simulations as devices trying to fulfil one or two among three incompatible epistemic values (precision, realism, genericity).

Year:  2014        PMID: 25515264     DOI: 10.1007/s40656-014-0005-2

Source DB:  PubMed          Journal:  Hist Philos Life Sci        ISSN: 0391-9714            Impact factor:   1.205


  1 in total

1.  Morphological Phylogenetics Evaluated Using Novel Evolutionary Simulations.

Authors:  Joseph N Keating; Robert S Sansom; Mark D Sutton; Christopher G Knight; Russell J Garwood
Journal:  Syst Biol       Date:  2020-09-01       Impact factor: 15.683

  1 in total

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