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Abstract
Natural evolution keeps inventing new complex and intricate forms and behaviors. Digital evolution and genetic algorithms fail to create the same kind of complexity, not just because we still lack the computational resources to rival nature, but because (it has been argued) we have not understood in principle how to create open-ended evolving systems. Much effort has been made to define such open-endedness so as to create forms of increasing complexity indefinitely. Here, however, a simple evolving computational system that satisfies all such requirements is presented. Doing so reveals a shortcoming in the definitions for open-ended evolution. The goal to create models that rival biological complexity remains. This work suggests that our current definitions allow for even simple models to pass as open-ended, and that our definitions of complexity and diversity are more important for the quest of open-ended evolution than the fact that something runs indefinitely.
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Affiliation(s)
- Arend Hintze
- Michigan State University, Department of Integrative Biology, Department of Computer Science and Engineering, BEACON Center for the Study of Evolution in Action.
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2
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Tamò G, Maesani A, Träger S, Degiacomi MT, Floreano D, Dal Peraro M. Disentangling constraints using viability evolution principles in integrative modeling of macromolecular assemblies. Sci Rep 2017; 7:235. [PMID: 28331186 PMCID: PMC5427971 DOI: 10.1038/s41598-017-00266-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 02/14/2017] [Indexed: 11/22/2022] Open
Abstract
Predicting the structure of large molecular assemblies remains a challenging task in structural biology when using integrative modeling approaches. One of the main issues stems from the treatment of heterogeneous experimental data used to predict the architecture of native complexes. We propose a new method, applied here for the first time to a set of symmetrical complexes, based on evolutionary computation that treats every available experimental input independently, bypassing the need to balance weight components assigned to aggregated fitness functions during optimization.
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Affiliation(s)
- Giorgio Tamò
- Laboratory for Biomolecular Modeling, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, CH-1015, Switzerland
| | - Andrea Maesani
- Laboratory of Intelligent Systems, Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland
| | - Sylvain Träger
- Laboratory for Biomolecular Modeling, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, CH-1015, Switzerland
| | - Matteo T Degiacomi
- Chemistry Research Laboratory, Department of Chemistry, University of Oxford, Oxford, UK
| | - Dario Floreano
- Laboratory of Intelligent Systems, Institute of Microengineering, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland.
| | - Matteo Dal Peraro
- Laboratory for Biomolecular Modeling, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, CH-1015, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, CH-1015, Switzerland.
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3
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Sun J, Garibaldi JM, Zhang Y, Al-Shawabkeh A. A multi-cycled sequential memetic computing approach for constrained optimisation. Inf Sci (N Y) 2016. [DOI: 10.1016/j.ins.2016.01.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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4
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Doncieux S, Bredeche N, Mouret JB, Eiben AE(G. Evolutionary Robotics: What, Why, and Where to. Front Robot AI 2015. [DOI: 10.3389/frobt.2015.00004] [Citation(s) in RCA: 123] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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