↓ Skip to main content

PLOS

Environmental Influence on the Evolution of Morphological Complexity in Machines

Overview of attention for article published in PLoS Computational Biology, January 2014
Altmetric Badge

Mentioned by

news
4 news outlets
blogs
3 blogs
twitter
17 X users
facebook
3 Facebook pages
googleplus
1 Google+ user
reddit
1 Redditor
q&a
1 Q&A thread
video
1 YouTube creator

Citations

dimensions_citation
97 Dimensions

Readers on

mendeley
125 Mendeley
citeulike
3 CiteULike
Title
Environmental Influence on the Evolution of Morphological Complexity in Machines
Published in
PLoS Computational Biology, January 2014
DOI 10.1371/journal.pcbi.1003399
Pubmed ID
Authors

Joshua E. Auerbach, Josh C. Bongard

Abstract

Whether, when, how, and why increased complexity evolves in biological populations is a longstanding open question. In this work we combine a recently developed method for evolving virtual organisms with an information-theoretic metric of morphological complexity in order to investigate how the complexity of morphologies, which are evolved for locomotion, varies across different environments. We first demonstrate that selection for locomotion results in the evolution of organisms with morphologies that increase in complexity over evolutionary time beyond what would be expected due to random chance. This provides evidence that the increase in complexity observed is a result of a driven rather than a passive trend. In subsequent experiments we demonstrate that morphologies having greater complexity evolve in complex environments, when compared to a simple environment when a cost of complexity is imposed. This suggests that in some niches, evolution may act to complexify the body plans of organisms while in other niches selection favors simpler body plans.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Switzerland 1 <1%
Netherlands 1 <1%
France 1 <1%
Germany 1 <1%
Costa Rica 1 <1%
India 1 <1%
Japan 1 <1%
United Kingdom 1 <1%
Other 0 0%
Unknown 112 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 24%
Researcher 17 14%
Student > Master 16 13%
Student > Bachelor 11 9%
Professor 10 8%
Other 21 17%
Unknown 20 16%
Readers by discipline Count As %
Computer Science 43 34%
Agricultural and Biological Sciences 19 15%
Engineering 18 14%
Biochemistry, Genetics and Molecular Biology 5 4%
Physics and Astronomy 3 2%
Other 12 10%
Unknown 25 20%