The Computational Foundations of Collective Intelligence
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911145402564608 |
|---|---|
| author | Pilgrim, Charlie Morford, Joe Warren, Elizabeth Aellen, Mélisande Krupenye, Christopher Mann, Richard P Biro, Dora |
| author_facet | Pilgrim, Charlie Morford, Joe Warren, Elizabeth Aellen, Mélisande Krupenye, Christopher Mann, Richard P Biro, Dora |
| contents | Why do collectives outperform individuals when solving some problems? Fundamentally, collectives have greater computational resources with more sensory information, more memory, more processing capacity, and more ways to act. While greater resources present opportunities, there are also challenges in coordination and cooperation inherent in collectives with distributed, modular structures. Despite these challenges, we show how collective resource advantages lead directly to well-known forms of collective intelligence including the wisdom of the crowd, collective sensing, division of labour, and cultural learning. Our framework also generates testable predictions about collective capabilities in distributed reasoning and context-dependent behavioural switching. Through case studies of animal navigation and decision-making, we demonstrate how collectives leverage their computational resources to solve problems not only more effectively than individuals, but by using qualitatively different problem-solving strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_07999 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Computational Foundations of Collective Intelligence Pilgrim, Charlie Morford, Joe Warren, Elizabeth Aellen, Mélisande Krupenye, Christopher Mann, Richard P Biro, Dora Neurons and Cognition Artificial Intelligence Multiagent Systems Neural and Evolutionary Computing Adaptation and Self-Organizing Systems Physics and Society Why do collectives outperform individuals when solving some problems? Fundamentally, collectives have greater computational resources with more sensory information, more memory, more processing capacity, and more ways to act. While greater resources present opportunities, there are also challenges in coordination and cooperation inherent in collectives with distributed, modular structures. Despite these challenges, we show how collective resource advantages lead directly to well-known forms of collective intelligence including the wisdom of the crowd, collective sensing, division of labour, and cultural learning. Our framework also generates testable predictions about collective capabilities in distributed reasoning and context-dependent behavioural switching. Through case studies of animal navigation and decision-making, we demonstrate how collectives leverage their computational resources to solve problems not only more effectively than individuals, but by using qualitatively different problem-solving strategies. |
| title | The Computational Foundations of Collective Intelligence |
| topic | Neurons and Cognition Artificial Intelligence Multiagent Systems Neural and Evolutionary Computing Adaptation and Self-Organizing Systems Physics and Society |
| url | https://arxiv.org/abs/2509.07999 |