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Complexity and Evolution

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

Deadline for manuscript submissions: closed (20 June 2021) | Viewed by 31546

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Prof. Dr. Francis Heylighen

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Guest Editor

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

Dr. Tomas Veloz

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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
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Dr. Olaf Witkowski

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Guest Editor

1. Cross Labs, Cross Compass Ltd., Shinkawa 2-9-11-9F, Chuo-ku, Tokyo 104-0033, Japan
2. Earth-Life Science Institute, Tokyo Institute of Technology, 2-12-1-IE-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan
3. College of Arts and Sciences, University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
Interests: artificial life; collective intelligence; open-ended evolution; emergence of communication; cognitive robotics; computational linguistics; origins of life

Ms. Daniela Flores

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Assistant Guest Editor

1. Fundacion para el Desarrollo Interdisciplinario de la Ciencia, la Tecnologia y las Artes, Santiago, Chile
2. Facultad de Ciencias, Departamento de biología, Universidad de Chile, Las Palmeras 3425, Ñuñoa, Santiago, Chile
Interests: I am interested in evodevo (evolution and development) related to the organismal form and shape, and the stability of form during ontogeny, and its influence acting as constraints and promoters in the evolutionary process. I am also interested in diverse evolutionary phenomena based on the interrelationship of unities of life to generate evolutionary innovations, such as endosymbiosis and the emergence of multicellularity.

Special Issue Information

The understanding of evolutionary processes is one 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 undergoing and a posterior form where the evolutionary process has been triggered. Most advanced methods to understand the emergence of evolutionary processes require the consideration of systemic features such as self-organization, resilience, and contextuality, among others.

In order to address the multiple facets of evolution, it is necessary to propose and apply methods that on the one hand incorporate recent advances in the modeling of complex systems, and on the other hand 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 any of these 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.

Prof. Dr. Francis Heylighen
Dr. Tomas Veloz
Dr. Olaf Witkowski
Ms. Daniela Flores
Guest Editors

Manuscript Submission Information

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Related Special Issue

Complexity and Evolution, 2nd Edition in Entropy (1 article)

Published Papers (9 papers)

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Editorial

Jump to: Research

3 pages, 165 KiB

Open AccessEditorial

Complexity and Evolution

by Tomas Veloz, Francis Heylighen and Olaf Witkowski

Entropy 2023, 25(2), 286; https://doi.org/10.3390/e25020286 - 3 Feb 2023

Viewed by 2043

Abstract

Understanding the underlying structure of evolutionary processes is one the most important issues of scientific enquiry of this century [...] Full article

(This article belongs to the Special Issue Complexity and Evolution)

Research

Jump to: Editorial

22 pages, 4173 KiB

Open AccessArticle

Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model

by Lakshwin Shreesha and Michael Levin

Entropy 2023, 25(1), 131; https://doi.org/10.3390/e25010131 - 9 Jan 2023

Cited by 10 | Viewed by 3981

Abstract

Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is cellular competency, since cells are not passive materials but descendants of unicellular organisms with complex context-sensitive behavioral capabilities. To probe the effects of different degrees of cellular competency on evolutionary dynamics, we used an evolutionary simulation in the context of minimal artificial embryogeny. Virtual embryos consisted of a single axis of positional information values provided by cells’ ‘structural genes’, operated upon by an evolutionary cycle in which embryos’ fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function (“regulative” development). We find that even minimal ability of cells with to improve their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that increasing the behavioral competency masks the raw fitness encoded by structural genes, with selection favoring improvements to its developmental problem-solving capacities over improvements to its structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. This kind of feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria. In addition, it identifies a possible driver for scaling intelligence over evolutionary time, and suggests strategies for engineering novel systems in silico and in bioengineering. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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16 pages, 910 KiB

Open AccessArticle

Modelling Worldviews as Stable Metabolisms

by Tomas Veloz and Pedro Maldonado

Entropy 2022, 24(10), 1476; https://doi.org/10.3390/e24101476 - 17 Oct 2022

Cited by 2 | Viewed by 1917

Abstract

The emergence and evolution of worldviews is a complex phenomenon that requires strong and rigorous scientific attention in our hyperconnected world. On the one hand, cognitive theories have proposed reasonable frameworks but have not reached general modeling frameworks where predictions can be tested. On the other hand, machine-learning-based applications perform extremely well at predicting outcomes of worldviews, but they rely on a set of optimized weights in a neural network that does not comply to a well-founded cognitive framework. In this article, we propose a formal approach used to investigate the establishment of and change in worldviews by recalling that the realm of ideas, where opinions, perspectives and worldviews are shaped, resemble, in many ways, a metabolic system. We propose a general modelization of worldviews based on reaction networks, and a specific starting model based on species representing belief attitudes and species representing belief change triggers. These two kinds of species combine and modify their structures through the reactions. We show that chemical organization theory combined with dynamical simulations can illustrate various interesting features of how worldviews emerge, are maintained and change. In particular, worldviews correspond to chemical organizations, meaning closed and self-producing structures, which are generally maintained by feedback loops occurring within the beliefs and triggers in the organization. We also show how, by inducing the external input of belief change triggers, it is possible to change from one worldview to another, in an irreversible way. We illustrate our approach with a simple example reflecting the formation of an opinion and a belief attitude about a theme, and, next, show a more complex scenario containing opinions and belief attitudes about two possible themes. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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16 pages, 3352 KiB

Open AccessArticle

Opinion Evolution in Divided Community

by Tomasz Weron and Janusz Szwabiński

Entropy 2022, 24(2), 185; https://doi.org/10.3390/e24020185 - 26 Jan 2022

Cited by 7 | Viewed by 2433

Abstract

Our agent-based model of opinion dynamics concerns the current vast divisions in modern societies. It examines the process of social polarization, understood here as the partition of a community into two opposing groups with contradictory opinions. Our goal is to measure how mutual animosities between parties may lead to their radicalization. We apply a double-clique topology with both positive and negative ties to the model of binary opinions. Individuals are subject to social pressure; they conform to the opinions of their own clique (positive links) and oppose those from the other one (negative links). There is also a chance of acting independently, which alters the system’s behavior in various ways, depending on its magnitude. The results, obtained with both Monte-Carlo simulations and the mean-field approach, lead to two main conclusions: in such a system, there exists a critical quantity of negative relations that are needed for polarization to occur, and (rather surprisingly) independent actions actually support the process, unless their frequency is too high, in which case the system falls into total disorder. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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27 pages, 493 KiB

Open AccessArticle

Are Words the Quanta of Human Language? Extending the Domain of Quantum Cognition

by Diederik Aerts and Lester Beltran

Entropy 2022, 24(1), 6; https://doi.org/10.3390/e24010006 - 21 Dec 2021

Cited by 10 | Viewed by 3911

Abstract

In previous research, we showed that ‘texts that tell a story’ exhibit a statistical structure that is not Maxwell–Boltzmann but Bose–Einstein. Our explanation is that this is due to the presence of ‘indistinguishability’ in human language as a result of the same words in different parts of the story being indistinguishable from one another, in much the same way that ’indistinguishability’ occurs in quantum mechanics, also there leading to the presence of Bose–Einstein rather than Maxwell–Boltzmann as a statistical structure. In the current article, we set out to provide an explanation for this Bose–Einstein statistics in human language. We show that it is the presence of ‘meaning’ in ‘texts that tell a story’ that gives rise to the lack of independence characteristic of Bose–Einstein, and provides conclusive evidence that ‘words can be considered the quanta of human language’, structurally similar to how ‘photons are the quanta of electromagnetic radiation’. Using several studies on entanglement from our Brussels research group, we also show, by introducing the von Neumann entropy for human language, that it is also the presence of ‘meaning’ in texts that makes the entropy of a total text smaller relative to the entropy of the words composing it. We explain how the new insights in this article fit in with the research domain called ‘quantum cognition’, where quantum probability models and quantum vector spaces are used in human cognition, and are also relevant to the use of quantum structures in information retrieval and natural language processing, and how they introduce ‘quantization’ and ‘Bose–Einstein statistics’ as relevant quantum effects there. Inspired by the conceptuality interpretation of quantum mechanics, and relying on the new insights, we put forward hypotheses about the nature of physical reality. In doing so, we note how this new type of decrease in entropy, and its explanation, may be important for the development of quantum thermodynamics. We likewise note how it can also give rise to an original explanatory picture of the nature of physical reality on the surface of planet Earth, in which human culture emerges as a reinforcing continuation of life. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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13 pages, 2163 KiB

Open AccessArticle

Computational Power of Asynchronously Tuned Automata Enhancing the Unfolded Edge of Chaos

by Yukio-Pegio Gunji and Daisuke Uragami

Entropy 2021, 23(11), 1376; https://doi.org/10.3390/e23111376 - 20 Oct 2021

Cited by 6 | Viewed by 1752

Abstract

Asynchronously tuned elementary cellular automata (AT-ECA) are described with respect to the relationship between active and passive updating, and that spells out the relationship between synchronous and asynchronous updating. Mutual tuning between synchronous and asynchronous updating can be interpreted as the model for dissipative structure, and that can reveal the critical property in the phase transition from order to chaos. Since asynchronous tuning easily makes behavior at the edge of chaos, the property of AT-ECA is called the unfolded edge of chaos. The computational power of AT-ECA is evaluated by the quantitative measure of computational universality and efficiency. It shows that the computational efficiency of AT-ECA is much higher than that of synchronous ECA and asynchronous ECA. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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15 pages, 313 KiB

Open AccessArticle

Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms

by Evo Busseniers, Tomas Veloz and Francis Heylighen

Entropy 2021, 23(8), 1039; https://doi.org/10.3390/e23081039 - 12 Aug 2021

Cited by 14 | Viewed by 3108

Abstract

In this article, we attempt at developing a scenario for the self-organization of goal-directed systems out of networks of (chemical) reactions. Related scenarios have been proposed to explain the origin of life starting from autocatalytic sets, but these sets tend to be too unstable and dependent on their environment to maintain. We apply instead a framework called Chemical Organization Theory (COT), which shows mathematically under which conditions reaction networks are able to form self-maintaining, autopoietic organizations. We introduce the concepts of perturbation, action, and goal based on an operationalization of the notion of change developed within COT. Next, we incorporate the latter with notions native to the theory of cybernetics aimed to explain goal directedness: reference levels and negative feedback among others. To test and refine these theoretical results, we present some examples that illustrate our approach. We finally discuss how this could result in a realistic, step-by-step scenario for the evolution of goal directedness, thus providing a theoretical solution to the age-old question of the origins of purpose. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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13 pages, 1187 KiB

Open AccessCommunication

Earth’s Complexity Is Non-Computable: The Limits of Scaling Laws, Nonlinearity and Chaos

by Sergio Rubin and Michel Crucifix

Entropy 2021, 23(7), 915; https://doi.org/10.3390/e23070915 - 19 Jul 2021

Cited by 7 | Viewed by 5327

Abstract

Current physics commonly qualifies the Earth system as ‘complex’ because it includes numerous different processes operating over a large range of spatial scales, often modelled as exhibiting non-linear chaotic response dynamics and power scaling laws. This characterization is based on the fundamental assumption that the Earth’s complexity could, in principle, be modeled by (surrogated by) a numerical algorithm if enough computing power were granted. Yet, similar numerical algorithms also surrogate different systems having the same processes and dynamics, such as Mars or Jupiter, although being qualitatively different from the Earth system. Here, we argue that understanding the Earth as a complex system requires a consideration of the Gaia hypothesis: the Earth is a complex system because it instantiates life—and therefore an autopoietic, metabolic-repair (M,R) organization—at a planetary scale. This implies that the Earth’s complexity has formal equivalence to a self-referential system that inherently is non-algorithmic and, therefore, cannot be surrogated and simulated in a Turing machine. We discuss the consequences of this, with reference to in-silico climate models, tipping points, planetary boundaries, and planetary feedback loops as units of adaptive evolution and selection. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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19 pages, 1184 KiB

Open AccessArticle

Causal Reasoning and Event Cognition as Evolutionary Determinants of Language Structure

by Peter Gärdenfors

Entropy 2021, 23(7), 843; https://doi.org/10.3390/e23070843 - 30 Jun 2021

Cited by 5 | Viewed by 4440

Abstract

The aim of this article is to provide an evolutionarily grounded explanation of central aspects of the structure of language. It begins with an account of the evolution of human causal reasoning. A comparison between humans and non-human primates suggests that human causal cognition is based on reasoning about the underlying forces that are involved in events, while other primates hardly understand external forces. This is illustrated by an analysis of the causal cognition required for early hominin tool use. Second, the thinking concerning forces in causation is used to motivate a model of human event cognition. A mental representation of an event contains two vectors representing a cause as well as a result but also entities such as agents, patients, instruments and locations. The fundamental connection between event representations and language is that declarative sentences express events (or states). The event structure also explains why sentences are constituted of noun phrases and verb phrases. Finally, the components of the event representation show up in language, where causes and effects are expressed by verbs, agents and patients by nouns (modified by adjectives), locations by prepositions, etc. Thus, the evolution of the complexity of mental event representations also provides insight into the evolution of the structure of language. Full article

(This article belongs to the Special Issue Complexity and Evolution)

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