Organizers

Introduction

Collective intelligence refers to the emergent ability of systems composed of many interacting agents—whether biological, social, or artificial—to solve complex problems, adapt to changes, and exhibit coordinated behaviour without centralized control. In biological systems, examples include the coordinated flocking of birds, schooling of fish, or the division of labour in honeybee colonies, where individuals communicate through pheromones and perform specialized roles to enhance colony efficiency. 

Applying the principles of Statistical Physics, the natural macroscopic behaviours or patterns can be modelled and explained by examining microscopic local interactions. By understanding the key components of biological collective systems, we can design the artificial counterpart, like in multi-agent artificial intelligence and swarm robotics, where collective intelligence enables robust and scalable solutions in dynamic environments. 

Key properties of collective intelligence include resilience, allowing the system to continue functioning effectively despite the failure or loss of individual agents; heterogeneity, where agents possess diverse capabilities; and adaptability, ensuring the system can respond flexibly to environmental changes or new challenges.

These systems are often characterized by underlying networks with complex dynamic topology that allows for the constant reshaping of connections between agents as tasks and environments change. The study of dynamical processes on complex networks—such as information dissemination, decision-making, and resource allocation—reveals how collective intelligence can emerge from simple local interactions, producing sophisticated global behaviour. 

This satellite event, with its keynote speakers, covers the complete journey from Biology to Artificial Intelligence and Robotics, rooted in the principles of Statistical Physics. 

Goals

This satellite will provide the right place for gathering researchers working in the field of collective intelligence from different disciplines such as Biology, Physics, Social Sciences, Artificial Intelligence and Robotics, with the following objectives:

Promote Interdisciplinary Exchange: Facilitate the sharing of knowledge between researchers in biology, social sciences, artificial intelligence, and robotics, discussing a platform for multi-disciplinary learning and collaboration on collective intelligence systems.

Investigate cross-disciplinary Collective Intelligence Principles: Explore the fundamental mechanisms driving collective intelligence in both biological and artificial systems, focusing on key properties such as resilience, adaptability, and heterogeneity.

Bridge Biological and Artificial Systems: Encourage the integration of insights from natural systems (e.g., animal behavior, social networks) into the design of artificial systems like swarm robotics and multi-agent AI, fostering innovation through bio-inspired approaches.

Topics

• • Collective animal behaviour

• • Collective artificial intelligence

• • Bioinspired collective systems

• • Swarm intelligence

• • Physics of behavior

• •          Emergent Phenomena 

• •          Biohybrid systems 

• • Animal social networks

• • Algorithms of Collective Intelligence

CALL FOR ABSTRACTS (CLOSED)

Use the dedicated page

Important Dates

• March 20, 2025:  Abstract submission deadline

• April 20, 2025:  Results for the abstract selection

• July 20, 2025 :  Early bird registration to CCS2025

• September 3, 2025: Satellite event

Registration

To join the satellite, registration to the CCS2025 main conference is mandatory, either for the full conference or for satellite events only. 

On site registration will be possible only upon availability. Make sure you register at: https://ccs25.cssociety.org/registration/