Evolution of Community Complexity
A Special Issue of Entropy (ISSN 1099-4300) belonging to the section "Complexity".
Deadline for manuscript submissions: closed (15 February 2026) | Viewed by 2779
Editors
Interests: open-ended evolution; life–mind continuity; offloaded agency; complex systems; artificial life
Special Issues, Collections and Topics in MDPI journals
Interests: information theory; complex systems; collective behaviors of microbes; dyadic human interactions; generative deep neural networks
Special Issue Information
Dear Colleagues,
This Special Issue aims to advance the understanding of novel behaviors and collective intelligence at the group level by developing a unified theoretical framework. While deep learning has contributed to data classification and gene expression analysis has enhanced the understanding of cellular states, collective phenomena in biological and physical systems—such as the behaviors of social insects, birds, fish, and fireflies—remain challenging to interpret cohesively. Current approaches, including evolutionary ecology and statistical physics, provide valuable insights but lack an overarching theoretical model to integrate diverse data.
We propose the "Community First" hypothesis, which posits that the formation of groups leads to a second level of individuation, driving the evolution of diversity and autonomy. This hypothesis will be investigated through an interdisciplinary approach involving experimental biology and theoretical modeling. One central aspect of this research is analyzing the "hierarchical structure of mutual information" to decode the complexity of inter-individual relationships. By breaking mutual information into redundancy, synergy, and uniqueness, we aim to provide new insights into how collective phenomena emerge and evolve.
This Special Issue seeks contributions that combine experimental, computational, and theoretical perspectives to explore collective dynamics and individuality. It particularly encourages studies leveraging novel data analysis methods to bridge the gap between empirical data and unified theories of collective intelligence.
Prof. Dr. Takashi Ikegami
Dr. Hiroki Kojima
Dr. Michael Crosscombe
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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
- complex systems
- collective intelligence
- evolutionary ecology
- community
- collective dynamics
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