The Computational Foundations of Collective Intelligence
September 06, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Charlie Pilgrim, Joe Morford, Elizabeth Warren, MΓ©lisande Aellen, Christopher Krupenye, Richard P Mann, Dora Biro
arXiv ID
2509.07999
Category
q-bio.NC
Cross-listed
cs.AI,
cs.MA,
cs.NE,
nlin.AO,
physics.soc-ph
Citations
0
Venue
arXiv.org
Last Checked
3 months ago
Abstract
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.
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