The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
How to Make Swarms Open-Ended? Evolving Collective Intelligence Through a Constricted Exploration of Adjacent Possibles
Open accessAbstract
We propose an approach to open-ended evolution via the simulation of swarm dynamics. In nature, swarms possess remarkable properties, which allow many organisms, from swarming bacteria to ants and flocking birds, to form higher-order structures that enhance their behavior as a group. Swarm simulations highlight three important factors to create novelty and diversity: (a) communication generates combinatorial cooperative dynamics, (b) concurrency allows for separation of time scales, and (c) complexity and size increases push the system towards transitions in innovation. We illustrate these three components in a model computing the continuous evolution of a swarm of agents. The results, divided into three distinct applications, show how emergent structures are capable of filtering information through the bottleneck of their memory, to produce meaningful novelty and diversity within their simulated environment.
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Communicative exploration can sustain open-ended collective novelty.
“Communicative exploration has also been shown to sustain open-ended collective novelty (Witkowski and Ikegami, 2019).”
From Social Reality Construction via Active Inference: Modeling the Dialectic of Conformity and Creativity (2026) · cites this paper as Witkowski and Ikegami, 2019
Section 5 (Discussion) reports that collective intelligence and limited communication channels produced new and diverse solutions in a swarm. But Section 4.1 says the results only suggest open-endedness and do not prove the phenomenon is truly open-ended, so the claim overstates what was shown about sustaining it. (LLM, conf=0.87)
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Citations
Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
The information bottleneck method
Tishby, N., Pereira, F. C., & Bialek, W. (2000) · arXiv · doi:10.48550/arxiv.physics/0004057 · Cited by 2,626 · cited 1×
“compared to a bottleneck that acts as a lter on several levels of the system, implementing computation that is not present in any of its parts. Part of this idea is analog to Tishby and Polani (1999) [46], where the information is squeezed through a bottleneck, to extract relevant or meaningful information from an env…”
BackgroundWhy Greatness Cannot Be Planned: The Myth of the Objective
Stanley, K. O., & Lehman, J. (2015) · doi:10.1007/978-3-319-15524-1 · Cited by 139
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Cited by
Sorted by citations
Nomura, K., & Horii, T. (2026) · ALIFE 2026: Proceedings of the 2026 Artificial Life Conference · doi:10.1162/isal.a.1009
Social Reality Construction via Active Inference: Modeling the Dialectic of Conformity and Creativity
Nomura, K., & Horii, T. (2026) · arXiv
“Communicative exploration has also been shown to sustain open-ended collective novelty (Witkowski and Ikegami, 2019).”
Metadata
- Authors
- Witkowski, O., & Ikegami, T.
- Affiliations
- Tokyo Institute of Technology (JP)
- The University of Tokyo (JP)
- Venue
- Artificial Life
- Publisher
- MIT Press
- Published
- 2019-05
- Volume
- 25
- Issue
- 2
- Pages
- 178-197
- ISSN
- 1064-5462 (ISSN-L)
- 1530-9185
- OpenAlex
- W2963600110
- Cited by
- 14
- References
- 3
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 3 · 2021: 2 · 2020: 2 · 2019: 2
- FWCI
- 0.84
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Artificial Life (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Japan Society for the Promotion of Science (17H01249)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Physical Sciences › Computer Science › Artificial Intelligence › Evolutionary Algorithms and Applications
- Keywords
- swarm simulation, open-ended evolution, collective intelligence, swarm dynamics, emergent structure, communication, concurrency, time scales, swarm size, memory bottleneck, agent-based modeling, innovation transition
- MeSH terms
- Animals, Animal Communication, Communication, Computer Simulation, Cooperative Behavior, Biological Evolution, Intelligence, Microbial Interactions
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