We are organizing an international Conference on Complex Systems and Stochastic Processes to be held from the 1st to the 5th of July 2024, hosted by the Universidad de Guadalajara at the University Center for Exact and Engineering Sciences (CUCEI) in Guadalajara, Jalisco, Mexico. The scope of the Meeting is to discuss recent exciting developments in critical dynamics, quantum thermodynamics, classical and quantum walks, sociophysics and opinion dynamics, search and optimization, econophysics, networks, fractals, among others.
Author: cxdig
Foundational Papers in Complexity Science
Foundational Papers in Complexity Science maps the development of complex-systems science through eighty-eight revolutionary works originally published between 1922 and 2000. Curated by SFI President David C. Krakauer, each seminal paper is introduced and placed into its historical context, with enduring insights discussed by leading contemporary complexity scientists.
These four volumes are a product of collective intelligence. More than a compilation, Foundational Papers represents large-scale collaboration within the SFI community—brilliant thinkers who have contextualized the work that shaped their own research, resulting in a sparkling demonstration of how complexity shatters the usual scientific divisions and a look back at the path we’ve followed in order to gain a clearer view of what lies ahead.
Read the full article at: www.foundationalpapersincomplexityscience.org
On principles of emergent organization
Adam Rupe, James P. Crutchfield
Physics Reports
Volume 1071, 13 June 2024, Pages 1-47
After more than a century of concerted effort, physics still lacks basic principles of spontaneous self-organization. To appreciate why, we first state the problem, outline historical approaches, and survey the present state of the physics of self-organization. This frames the particular challenges arising from mathematical intractability and the resulting need for computational approaches, as well as those arising from a chronic failure to define structure. Then, an overview of two modern mathematical formulations of organization—intrinsic computation and evolution operators—lays out a way to overcome these challenges. Additionally, we show how intrinsic computation and evolution operators combine to produce a general framework showing physical consistency between emergent behaviors and their underlying physics. This statistical mechanics of emergence provides a theoretical foundation for data-driven approaches to organization necessitated by analytic intractability. Taken all together, the result is a constructive path towards principles of organization that builds on the mathematical identification of structure.
Read the full article at: www.sciencedirect.com
Non-Spatial Hash Chemistry as a Minimalistic Open-Ended Evolutionary System
Hiroki Sayama
There is an increasing level of interest in open-endedness in the recent literature of Artificial Life and Artificial Intelligence. We previously proposed the cardinality leap of possibility spaces as a promising mechanism to facilitate open-endedness in artificial evolutionary systems, and demonstrated its effectiveness using Hash Chemistry, an artificial chemistry model that used a hash function as a universal fitness evaluator. However, the spatial nature of Hash Chemistry came with extensive computational costs involved in its simulation, and the particle density limit imposed to prevent explosion of computational costs prevented unbounded growth in complexity of higher-order entities. To address these limitations, here we propose a simpler non-spatial variant of Hash Chemistry in which spatial proximity of particles are represented explicitly in the form of multisets. This model modification achieved a significant reduction of computational costs in simulating the model. Results of numerical simulations showed much more significant unbounded growth in both maximal and average sizes of replicating higher-order entities than the original model, demonstrating the effectiveness of this non-spatial model as a minimalistic example of open-ended evolutionary systems.
Read the full article at: arxiv.org
Making Sense of Chaos: A Better Economics for a Better World, by J. Doyne Farmer
We live in an age of increasing complexity, where accelerating technology and global interconnection hold more promise – and more peril – than any other time in human history. As well as financial crises, issues around climate change, automation, growing inequality and polarization are all rooted in the economy, yet standard economic predictions fail us.
Many books have been written about Doyne Farmer and his pioneering work in chaos and complexity theory. Making Sense of Chaos is the first in his own words, presenting a manifesto for doing economics better. In a tale of science and ideas, Farmer fuses his profound knowledge with stories from his life to explain how to harness a scientific revolution to address the economic conundrums facing society.
Using big data and ever more powerful computers, we can for the first time apply complex systems science to economic activity, building realistic models of the global economy. The resulting simulations and the emergent behaviour we observe form the cornerstone of complexity economics. This new science, Farmer shows, will allow us to test ideas and make significantly better economic predictions – and, ultimately, create a better world.
More at: www.penguin.co.uk
