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Complexity and Evolution, 2nd Edition

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: 11 December 2024 | Viewed by 3095

Special Issue Editors


E-Mail Website
Guest Editor
Center Leo Apostel, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Interests: self-organization; collective intelligence; cybernetics; complex adaptive systems; distributed cognition

E-Mail Website
Guest Editor
1. Center Leo Apostel, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
2. Departamento de Matemáticas, Universidad Tecnológica Metropolitana, Las Palmeras 3360, 7800003 Ñuñoa, Chile
3. Fundación para el Desarrollo Interdisciplinario de la Ciencia, la Tecnología y las Artes, 8330307 Santiago, Chile
Interests: cognitive science; reaction networks; quantum interaction; artificial intelligence; theory of concepts
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The understanding of evolutionary processes is one of the most important issues of scientific enquiry of this century. Scientific thinking in twentieth century witnessed the overwhelming power of the evolutionary paradigm. It not only solidified the foundations of diverse areas such as cell biology, ecology, and economics, but also fostered the development of several mathematical and computational tools to model and simulate how evolutionary processes take place.

Besides the application of the evolutionary paradigm and the discovery of the evolutionary features for diverse processes, there is another interesting aspect which touches upon the emergence of novel evolutionary processes. Generally, the emergence of an evolutionary process requires a complex transition between a prior form where no evolutionary process is occurring and a posterior form where the evolutionary process has been triggered. Most advanced methods used to understand the emergence of evolutionary processes require the consideration of systemic features such as self-organization, autopoiesis, resilience, goal-directedness, etc.

To address these aspects in evolutionary theories, it is necessary to propose and apply methods that both incorporate recent advances in the modeling of complex systems and leverage both the increasing modeling power as well as growth and integration of databases associated with evolutionary processes. We welcome interdisciplinary articles that aim to advance our understanding of the role played by complexity in the evolution of natural and artificial processes. We welcome articles related to the following topics:

  • Biological evolution;
  • Cognitive evolution;
  • Social evolution;
  • Evolutionary processes of artificial systems;
  • The emergence of evolutionary processes;
  • Novel methods to study the structural properties of evolutionary processes.

Dr. Francis Heylighen
Dr. Tomas Veloz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biological evolution
  • cognitive evolution
  • social evolution

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Published Papers (1 paper)

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Research

44 pages, 10685 KiB  
Article
Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales
by Benedikt Hartl, Sebastian Risi and Michael Levin
Entropy 2024, 26(7), 532; https://doi.org/10.3390/e26070532 - 21 Jun 2024
Cited by 1 | Viewed by 2765
Abstract
In recent years, the scientific community has increasingly recognized the complex multi-scale competency architecture (MCA) of biology, comprising nested layers of active homeostatic agents, each forming the self-orchestrated substrate for the layer above, and, in turn, relying on the structural and functional plasticity [...] Read more.
In recent years, the scientific community has increasingly recognized the complex multi-scale competency architecture (MCA) of biology, comprising nested layers of active homeostatic agents, each forming the self-orchestrated substrate for the layer above, and, in turn, relying on the structural and functional plasticity of the layer(s) below. The question of how natural selection could give rise to this MCA has been the focus of intense research. Here, we instead investigate the effects of such decision-making competencies of MCA agential components on the process of evolution itself, using in silico neuroevolution experiments of simulated, minimal developmental biology. We specifically model the process of morphogenesis with neural cellular automata (NCAs) and utilize an evolutionary algorithm to optimize the corresponding model parameters with the objective of collectively self-assembling a two-dimensional spatial target pattern (reliable morphogenesis). Furthermore, we systematically vary the accuracy with which the uni-cellular agents of an NCA can regulate their cell states (simulating stochastic processes and noise during development). This allows us to continuously scale the agents’ competency levels from a direct encoding scheme (no competency) to an MCA (with perfect reliability in cell decision executions). We demonstrate that an evolutionary process proceeds much more rapidly when evolving the functional parameters of an MCA compared to evolving the target pattern directly. Moreover, the evolved MCAs generalize well toward system parameter changes and even modified objective functions of the evolutionary process. Thus, the adaptive problem-solving competencies of the agential parts in our NCA-based in silico morphogenesis model strongly affect the evolutionary process, suggesting significant functional implications of the near-ubiquitous competency seen in living matter. Full article
(This article belongs to the Special Issue Complexity and Evolution, 2nd Edition)
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