Swarm Models: From Biological and Social to Artificial Systems
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: closed (20 September 2021) | Viewed by 18269
Special Issue Editors
Interests: complex systems; statistical physics; nonlinear dynamics
Special Issue Information
In nature, many animals show collective behavior despite the absence of a central authority; insects (for example bees, ants, cockroaches), birds, fish, as well as groups of people show emerging collective choices as a result of their social interactions. A global decision is taken in response to a change or stimulus from the environment, occurring only through local communication between a few individuals and resulting in the appearance of coordinated and self-organized behavior. This behavior has been optimized by evolution in order to cater more efficiently to the special needs of the species (like foraging) or to react faster to sudden dangers. In robotics, a new field termed swarm robotics, that takes inspiration from these examples from biology and social sciences, has been used to design the collective decision making of robots in such applications where the use of a large number of robots is beneficial. Some examples are in the environmental monitoring of large areas, rescue missions in remote environments, and smart agriculture. In comparison to use of a single robot, the use of a swarm of robots guarantees flexibility, resiliency, and scalability.
This Special Issue aims to join together the different communities looking at collective behavior from their different perspectives, examining the spectrum from natural to artificial systems. We are looking for contributions on collective behavior from the point of view of statistical physics to study the dynamics of natural and social systems and/or to optimize the design of those that are artificial. Possible topics of interest include collective decision making in biological, social, and robotic systems; swarm robotics; self-organization; study of simple to complex interaction network topologies in swarms; application of information theory; entropy and other complexity metrics to study information transfer in swarms; and evolution of communication and coordination in self-organized swarms of agents or robots.
Dr. Giulia De Masi
Dr. Eliseo Ferrante
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
- swarm models
- collective decision making
- collective behavior
- flocking
- biological inspired artificial swarms
- complex networks
- self-organization
- information theory
- entropy
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.