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Author Marshall, James A. R. ♦ Zenil, Hector
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract While evolution has inspired algorithmic methods of heuristic optimization, little has been done in the way of using concepts of computation to advance our understanding of salient aspects of biological phenomena. The authors argue under reasonable assumptions, interesting conclusions can be drawn that are of relevance to behavioral evolution. The authors will focus on two important features of life---robustness and fitness---which, they will argue, are related to algorithmic probability and to the thermodynamics of computation, disciplines that may be capable of modeling key features of living organisms, and which can be used in formulating new algorithms of evolutionary computation.
Description Affiliation: University of Sheffield (Marshall, James A. R.) || University of Sheffield and Algorithmic Nature Group (Zenil, Hector)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-06-29
Publisher Place New York
Journal Ubiquity (UBIQ)
Volume Number 2013
Issue Number April
Page Count 16
Starting Page 1
Ending Page 16


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Source: ACM Digital Library