Special Issue "The Role of Information in Cultural Evolution"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (15 April 2022) | Viewed by 11127

Special Issue Editors

Dr. Vanessa Ferdinand
E-Mail Website
Guest Editor
Melbourne School of Psychological Sciences, University of Melbourne, Parkville, VIC 3010, Australia
Interests: cultural evolution; computational cognitive science; natural information processing; philosophy of biology
Dr. Sarah Marzen
E-Mail Website
Guest Editor
Keck Science Center at the Claremont Colleges, Claremont McKenna Colleges, Claremont, CA 91711, USA
Interests: biophysics; machine learning; bio-inspired computing; information theory
Dr. Helena Miton
E-Mail Website
Guest Editor
Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
Interests: computational social science; cognition; cognitive anthropology; cultural evolution; historical dynamics
Dr. Noga Zaslavsky
E-Mail Website
Guest Editor
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA
Interests: information theory for cognitive systems; machine learning; computational cognitive science; computational linguistics
Prof. Dr. Martin Hilbert
E-Mail Website
Guest Editor
Department of Communication, GG Computer Science, University of California, 370 Kerr Hall, 1 Shields Avenue, Davis, CA 95616, USA
Interests: computational social science; digitalization; algorithmification; complex social systems; international development; United Nations; computational mechanics; social change; mathematical theory of communication
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cultural evolution is an information processing system at two levels. At the micro level, culture is sustained by the information-processing capabilities of cognitive agents who are able to perceive, process, and reproduce the information found in cultural artifacts and behaviors, such as technology, language, music, and art. At the macro level, culture is an evolutionary process that discovers and stores information about good solutions to hard problems that humans and animals face as they struggle to survive in the world.

We welcome original research articles and reviews that focus on the role of information in culturally evolving systems and populations. We will consider all examples in humans, animals, and artificial information processing systems that transmit observable behaviors or artifacts that change over time, simulations or mathematical models of cultural evolution, and any reviews or philosophy of biology treatments of the following topics:

  • The information content of cultural artifacts and its transmissibility;
  • The role of cognitive biases and cognitive information processing in cultural evolution;
  • The emergence of replicators or high-fidelity cultural transmission;
  • Demonstrations of optimal compression in cultural artifacts, such as semantic systems;
  • Information-theoretic approaches to language evolution;
  • Social learning processes and the emergence or retention of cultural information;
  • Information flow or diffusion in real-world networks of evolving cultural artifacts;
  • Collective information processing in groups, institutions, or networks of agents;
  • Information-theoretic approaches to creativity, novel variation, or design space exploration;
  • Any treatment of cultural evolution as an information processing system.

Dr. Vanessa Ferdinand
Dr. Sarah Marzen
Dr. Helena Miton
Dr. Noga Zaslavsky
Prof. Dr. Martin Hilbert
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 1800 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

  • cultural evolution
  • computational social science
  • information flow
  • replicators
  • optimal compression
  • cultural information

Published Papers (6 papers)

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Research

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Article
Communicative Efficiency or Iconic Learning: Do Acquisition and Communicative Pressures Interact to Shape Colour- Naming Systems?
Entropy 2022, 24(11), 1542; https://doi.org/10.3390/e24111542 - 26 Oct 2022
Viewed by 321
Abstract
Language evolution is driven by pressures for simplicity and informativity; however, the timescale on which these pressures operate is debated. Over several generations, learners’ biases for simple and informative systems can guide language evolution. Over repeated instances of dyadic communication, the principle of [...] Read more.
Language evolution is driven by pressures for simplicity and informativity; however, the timescale on which these pressures operate is debated. Over several generations, learners’ biases for simple and informative systems can guide language evolution. Over repeated instances of dyadic communication, the principle of least effort dictates that speakers should bias systems towards simplicity and listeners towards informativity, similarly guiding language evolution. At the same time, it has been argued that learners only provide a bias for simplicity and, thus, language users must provide a bias for informativity. To what extent do languages evolve during acquisition versus use? We address this question by formally defining and investigating the communicative efficiency of acquisition trajectories. We illustrate our approach using colour-naming systems, replicating a communicative efficiency model based on the information bottleneck problem, and an acquisition model based on self-organising maps. We find that to the extent that language is iconic, learning alone is sufficient to shape language evolution. Regarding colour-naming systems specifically, we find that incorporating learning biases into communicative efficiency accounts might explain how speakers and listeners trade off communicative effort. Full article
(This article belongs to the Special Issue The Role of Information in Cultural Evolution)
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Article
Quantifying the Selective, Stochastic, and Complementary Drivers of Institutional Evolution in Online Communities
Entropy 2022, 24(9), 1185; https://doi.org/10.3390/e24091185 - 25 Aug 2022
Cited by 1 | Viewed by 525
Abstract
Institutions and cultures usually evolve in response to environmental incentives. However, sometimes institutional change occurs due to stochastic drivers beyond current fitness, including drift, path dependency, blind imitation, and complementary cooperation in fluctuating environments. Disentangling the selective and stochastic components of social system [...] Read more.
Institutions and cultures usually evolve in response to environmental incentives. However, sometimes institutional change occurs due to stochastic drivers beyond current fitness, including drift, path dependency, blind imitation, and complementary cooperation in fluctuating environments. Disentangling the selective and stochastic components of social system change enables us to identify the key features of long-term organizational development. Evolutionary approaches provide organizational science with abundant theories to demonstrate organizational evolution by tracking beneficial or harmful features. In this study, focusing on 20,000 Minecraft communities, we measure these drivers empirically using two of the most widely applied evolutionary models: the Price equation and the bet-hedging model. As a result, we find strong selection pressure on administrative and information rules, suggesting that their positive correlation with community fitness is the main reason for their frequency change. We also find that stochastic drivers decrease the average frequency of administrative rules. The result makes sense when viewed in the context of evolutionary bet-hedging. We show through the bet-hedging result that institutional diversity contributes to the growth and stability of rules related to information, communication, and economic behaviors. Full article
(This article belongs to the Special Issue The Role of Information in Cultural Evolution)
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Article
WikiArtVectors: Style and Color Representations of Artworks for Cultural Analysis via Information Theoretic Measures
Entropy 2022, 24(9), 1175; https://doi.org/10.3390/e24091175 - 23 Aug 2022
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Abstract
With the increase in massive digitized datasets of cultural artefacts, social and cultural scientists have an unprecedented opportunity for the discovery and expansion of cultural theory. The WikiArt dataset is one such example, with over 250,000 high quality images of historically significant artworks [...] Read more.
With the increase in massive digitized datasets of cultural artefacts, social and cultural scientists have an unprecedented opportunity for the discovery and expansion of cultural theory. The WikiArt dataset is one such example, with over 250,000 high quality images of historically significant artworks by over 3000 artists, ranging from the 15th century to the present day; it is a rich source for the potential mining of patterns and differences among artists, genres, and styles. However, such datasets are often difficult to analyse and use for answering complex questions of cultural evolution and divergence because of their raw formats as image files, which are represented as multi-dimensional tensors/matrices. Recent developments in machine learning, multi-modal data analysis and image processing, however, open the door for us to create representations of images that extract important, domain-specific features from images. Art historians have long emphasised the importance of art style, and the colors used in art, as ways to characterise and retrieve art across genre, style, and artist. In this paper, we release a massive vector-based dataset of paintings (WikiArtVectors), with style representations and color distributions, which provides cultural and social scientists with a framework and database to explore relationships across these two vital dimensions. We use state-of-the-art deep learning and human perceptual color distributions to extract the representations for each painting, and aggregate them across artist, style, and genre. These vector representations and distributions can then be used in tandem with information-theoretic and distance metrics to identify large-scale patterns across art style, genre, and artist. We demonstrate the consistency of these vectors, and provide early explorations, while detailing future work and directions. All of our data and code is publicly available on GitHub. Full article
(This article belongs to the Special Issue The Role of Information in Cultural Evolution)
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Article
Restricted Access to Working Memory Does Not Prevent Cumulative Score Improvement in a Cultural Evolution Task
Entropy 2022, 24(3), 325; https://doi.org/10.3390/e24030325 - 24 Feb 2022
Viewed by 673
Abstract
Some theories propose that human cumulative culture is dependent on explicit, system-2, metacognitive processes. To test this, we investigated whether access to working memory is required for cumulative cultural evolution. We restricted access to adults’ working-memory (WM) via a dual-task paradigm, to assess [...] Read more.
Some theories propose that human cumulative culture is dependent on explicit, system-2, metacognitive processes. To test this, we investigated whether access to working memory is required for cumulative cultural evolution. We restricted access to adults’ working-memory (WM) via a dual-task paradigm, to assess whether this reduced performance in a cultural evolution task, and a metacognitive monitoring task. In total, 247 participants completed either a grid search task or a metacognitive monitoring task in conjunction with a WM task and a matched control. Participants’ behaviour in the grid search task was then used to simulate the outcome of iterating the task over multiple generations. Participants in the grid search task scored higher after observing higher-scoring examples, but could only beat the scores of low-scoring example trials. Scores did not differ significantly between the control and WM distractor blocks, although more errors were made when under WM load. The simulation showed similar levels of cumulative score improvement across conditions. However, scores plateaued without reaching the maximum. Metacognitive efficiency was low in both blocks, with no indication of dual-task interference. Overall, we found that taxing working-memory resources did not prevent cumulative score improvement on this task, but impeded it slightly relative to a control distractor task. However, we found no evidence that the dual-task manipulation impacted participants’ ability to use explicit metacognition. Although we found minimal evidence in support of the explicit metacognition theory of cumulative culture, our results provide valuable insights into empirical approaches that could be used to further test predictions arising from this account. Full article
(This article belongs to the Special Issue The Role of Information in Cultural Evolution)
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Review

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Review
Organizational Development as Generative Entrenchment
Entropy 2022, 24(7), 879; https://doi.org/10.3390/e24070879 - 26 Jun 2022
Viewed by 1020
Abstract
A critical task for organizations is how to best structure themselves to efficiently allocate information and resources to individuals tasked with solving sub-components of the organization’s central problems. Despite this criticality, the processes by which organizational structures form remain largely opaque within organizational [...] Read more.
A critical task for organizations is how to best structure themselves to efficiently allocate information and resources to individuals tasked with solving sub-components of the organization’s central problems. Despite this criticality, the processes by which organizational structures form remain largely opaque within organizational theory, with most approaches focused on how structure is influenced by individual managerial heuristics, normative cultural perceptions, and trial-and-error. Here, we propose that a broad understanding of organizational formation can be aided by appealing to generative entrenchment, a theory from developmental biology that helps explain why phylogenetically diverse animals appear similar as embryos. Drawing inferences from generative entrenchment and applying it to organizational differentiation, we argue that the reason many organizations appear structurally similar is due to core informational restraints on individual actors beginning at the top and descending to the bottom of these informational hierarchies, which reinforces these structures via feedback between separate levels. We further argue that such processes can lead to the emergence of a variety of group-level traits, an important but undertheorized class of phenomena in cultural evolution. Full article
(This article belongs to the Special Issue The Role of Information in Cultural Evolution)
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Other

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Concept Paper
Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments
Entropy 2022, 24(6), 819; https://doi.org/10.3390/e24060819 - 12 Jun 2022
Cited by 3 | Viewed by 2047
Abstract
One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the [...] Read more.
One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings. Full article
(This article belongs to the Special Issue The Role of Information in Cultural Evolution)
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