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Simulation of biological evolution and the NFL theorems

William Dembski (No free lunch: why specified complexity cannot be purchased without intelligence, 2002) claimed that the NFL theorems from optimization theory render darwinian biological evolution impossible. Häggström (Biology and Philosophy 22:217–230, 2007) argued that the NFL theorems are not r...

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Autor principal: Meester, Ronald
Formato: Texto
Lenguaje:English
Publicado: Springer Netherlands 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2837227/
https://www.ncbi.nlm.nih.gov/pubmed/20234823
http://dx.doi.org/10.1007/s10539-008-9134-x
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author Meester, Ronald
author_facet Meester, Ronald
author_sort Meester, Ronald
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description William Dembski (No free lunch: why specified complexity cannot be purchased without intelligence, 2002) claimed that the NFL theorems from optimization theory render darwinian biological evolution impossible. Häggström (Biology and Philosophy 22:217–230, 2007) argued that the NFL theorems are not relevant for biological evolution at all, since the assumptions of the NFL theorems are not met. Although I agree with Häggström (Biology and Philosophy 22:217–230, 2007), in this article I argue that the NFL theorems should be interpreted as dealing with an extreme case within a much broader context. This broader context is in fact relevant for scientific research of certain evolutionary processes; not in the sense that the theorems can be used to draw conclusions about any intelligent design inference, but in the sense that it helps us to interpret computer simulations of evolutionary processes. As a result of this discussion, I will argue that from simulations, we do not learn much about how complexity arises in the universe. This position is in contrast with certain claims in the literature that I will discuss.
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spelling pubmed-28372272010-03-15 Simulation of biological evolution and the NFL theorems Meester, Ronald Biol Philos Article William Dembski (No free lunch: why specified complexity cannot be purchased without intelligence, 2002) claimed that the NFL theorems from optimization theory render darwinian biological evolution impossible. Häggström (Biology and Philosophy 22:217–230, 2007) argued that the NFL theorems are not relevant for biological evolution at all, since the assumptions of the NFL theorems are not met. Although I agree with Häggström (Biology and Philosophy 22:217–230, 2007), in this article I argue that the NFL theorems should be interpreted as dealing with an extreme case within a much broader context. This broader context is in fact relevant for scientific research of certain evolutionary processes; not in the sense that the theorems can be used to draw conclusions about any intelligent design inference, but in the sense that it helps us to interpret computer simulations of evolutionary processes. As a result of this discussion, I will argue that from simulations, we do not learn much about how complexity arises in the universe. This position is in contrast with certain claims in the literature that I will discuss. Springer Netherlands 2008-09-23 2009 /pmc/articles/PMC2837227/ /pubmed/20234823 http://dx.doi.org/10.1007/s10539-008-9134-x Text en © The Author(s) 2008 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article
Meester, Ronald
Simulation of biological evolution and the NFL theorems
title Simulation of biological evolution and the NFL theorems
title_full Simulation of biological evolution and the NFL theorems
title_fullStr Simulation of biological evolution and the NFL theorems
title_full_unstemmed Simulation of biological evolution and the NFL theorems
title_short Simulation of biological evolution and the NFL theorems
title_sort simulation of biological evolution and the nfl theorems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2837227/
https://www.ncbi.nlm.nih.gov/pubmed/20234823
http://dx.doi.org/10.1007/s10539-008-9134-x
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