”Information Processing in Complex Systems”
The 12th International Conference on Guided Self-Organization takes place during October 14-15, 2026 in Binghamton, NY (USA), during The 2026 Conference on Complex Systems (CCS 2026) . GSO-2026 is organized by The State University of New York at Binghamton and The International Association for Guided Self-Organization (TIA-GSO).
Research Aims and Topics
GSO “aims to regulate self-organization for specific purposes, so that a dynamical system may reach specific attractors or outcomes. The regulation constrains a self-organizing process within a complex system by restricting local interactions between the system components, rather than following an explicit control mechanism or a global design blueprint.”
Information processing in complex self-organizing systems involves the storage, transfer, and modification of information through the interactions of components within the system. Unlike traditional computers, which process digital information in a centralized manner, complex systems like biological organisms or social networks process information in decentralized, distributed, and often analog ways. The study of information processing in complex systems seeks to define a set of universal properties that can describe the dynamics of diverse systems, from brain networks to financial markets, using a common language. Understanding information processing in complex systems is fundamental to designing self-organizing systems, engineering collective behavior and developing energetically efficient models of computation. Modern approaches use frameworks from fields such as information theory, dynamical systems, and machine learning to model how systems ranging from economies to ant colonies process information.
The GSO-2026 conference will bring together invited experts and researchers in unconventional computation, swarm intelligence, open-ended evolution, and complex adaptive systems. Special topics of interest include: synthetic and systems biology, agent-based modeling, evolutionary and adaptive computation, socio- and bio-inspired algorithms, swarm robotics, physics of self-organizing behavior, information-driven self-organization, and self-organizing cyber-physical systems.
More at: www.guided-self.org
Complexity Digest 