Author: cxdig

On the Positive Role of Noise and Error in Complex Systems

Roli, A.; Braccini, M.; Stano, P.

 Systems 2024, 12, 338.

Noise and error are usually considered to be disturbances negatively affecting the behavior of a system. Nevertheless, from a systemic perspective, taking into account openness and incompleteness of complex systems, noise and error may assume a creative, constructive, and positive role in that they are a source of novelty that can trigger the reorganization of the system, the growth of complexity, and the emergence of new meaning. Examples of this phenomenon can be found in evolutionary phenomena driven by affordances, the formation of new attractors in dynamic systems responding to external perturbations, and improvisation in music. We argue that it is possible to identify general properties that enable the positive effect of noise and errors in complex systems, namely, multilevel organization, redundancy, incompleteness, and criticality. These properties play a major role in living systems and can guide the design of robust and adaptive artificial systems.

Read the full article at: www.mdpi.com

Open Call – Conference Complex Systems (CCS 2026 and CCS 2027)

The Complex Systems Society (CSS) organizes every year a main conference (CCS) — the most important annual meeting for the complex systems research community.
The Complex Systems Society invites bids to host the 2026 and 2027 editions.
The conference is generally held in September/October of each year.

More at: cssociety.org

Inferring Local Interactions from Global Response in Condensed Active Matter

Binghamton Center of Complex Systems (CoCo) Seminar
September 25, 2024
Robert Wagner (Mechanical Engineering, Binghamton University)
“Inferring Local Interactions from Global Response in Condensed Active Matter: Complex Emergence in the Mechanics of Fire Ant Rafts”

Read the full article at: vimeo.com

Complex-Systems Research in Psychology, by Han L. J. van der Maas

Humans are the ultimate complex systems. In this monograph intended for psychologists and social scientists interested in modeling psychological processes, Han L. J. van der Maas argues that we can only succeed in exploring the psychological system by understanding its complexity. By applying the tools of complexity science to psychology, researchers and practitioners can achieve desperately needed breakthroughs in the social sciences.

The book has three primary objectives: to provide a comprehensive overview of complex-systems research, with a particular emphasis on its applications in psychology and the social sciences; to provide skills for complex-systems research; and to foster critical thinking regarding the potential applications of complex systems in psychology. Readers should have a basic understanding of mathematics and knowledge of the programming language R.

Complex-Systems Research in Psychology explores a range of topics, including chaos, bifurcation, and self-organization in psychological processes, psychological network analysis, as well as agent-based modeling of social processes. It offers applications in various areas of psychology, such as perception, depression, addiction, cognitive development, and polarization.

Download full book at: www.sfipress.org

Why collective behaviours self-organise to criticality: A primer on information-theoretic and thermodynamic utility measures

Qianyang Chen, Mikhail Prokopenko

Collective behaviours are frequently observed to self-organise to criticality. Existing proposals to explain these phenomena, such as Self-organised Criticality (SOC), are fragmented across disciplines and only partially answer the question. This paper investigates the underlying, intrinsic, utilities that may explain self-organisation of collective behaviours near criticality. We focus on information-driven approaches such as predictive information, empowerment, and active inference, as well as thermodynamic efficiency, which incorporates both information-theoretic and thermodynamic quantities. By interpreting the Ising model as a perception-action loop, we compare how different intrinsic utilities shape collective behaviour and analyse the distinct characteristics that arise when each is optimised. In particular, we highlight that at the critical regime thermodynamic efficiency balances the predictability gained by the system and its energy costs. Finally, we propose the Principle of Super-efficiency, suggesting that collective behaviours self-organise to the critical regime where optimal efficiency is achieved with respect to the entropy reduction relative to the thermodynamic costs.

Read the full article at: arxiv.org