Climate tipping points — too risky to bet against
Politicians, economists and even some natural scientists have tended to assume that tipping points in the Earth system — such as the loss of the Amazon rainforest or the West Antarctic ice sheet — are of low probability and little understood. Yet evidence is mounting that these events could be more likely than was thought, have high impacts and are interconnected across different biophysical systems, potentially committing the world to long-term irreversible changes.
Here we summarize evidence on the threat of exceeding tipping points, identify knowledge gaps and suggest how these should be plugged. We explore the effects of such large-scale changes, how quickly they might unfold and whether we still have any control over them.
In our view, the consideration of tipping points helps to define that we are in a climate emergency and strengthens this year’s chorus of calls for urgent climate action — from schoolchildren to scientists, cities and countries.
Source: www.nature.com
Introduction to Artificial Life for People who Like AI
Artificial Life, often shortened as ALife. What is your first thought when reading those words? A brand of T-shirts? A Greg Egan novel?
For me and hundreds of ALifers, ALife is the bottom-up scientific study of the fundamental principles of life. Just as Artificial Intelligence researchers ponder the nature of intelligence by trying to build intelligent systems from scratch, ALife researchers investigate the nature of “life” by trying to build living systems from scratch.
Source: thegradient.pub
Complex Systems Summer School 2020 | Santa Fe Institute
The SFI Complex Systems Summer School (CSSS) offers an intensive 4-week introduction to complex behavior in mathematical, physical, living, and social systems. Lectures are taught by the faculty of the Santa Fe Institute (SFI) and other leading educators and scholars. The school is for graduate students, postdoctoral fellows, and professionals seeking to transcend traditional disciplinary boundaries, take intellectual risks, and ask big questions about complex systems.
The program consists of an intensive series of lectures, labs, and discussions focusing on foundational concepts, tools, and current topics in complexity science. These include nonlinear dynamics, scaling theory, information theory, adaptation and evolution, networks, machine learning, agent-based models, and other topical areas and case studies. Participants collaborate in developing novel research projects throughout the four weeks of the program that culminate in final presentations and papers.
June 14 – July 10, 2020
Source: santafe.edu
Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
Complexity measures and information theory metrics in general have recently been attracting the interest of multi-agent and robotics communities, owing to their capability of capturing relevant features of robot behaviors, while abstracting from implementation details. We believe that theories and tools from complex systems science and information theory may be fruitfully applied in the near future to support the automatic design of robot swarms and the analysis of their dynamics. In this paper we discuss opportunities and open questions in this scenario.
Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
Andrea Roli1, Antoine Ligot and Mauro Birattari
Front. Robot. AI, 26 November 2019
Source: www.frontiersin.org
Hidden complexity in Life-like rules
An alternative way to study the rules of life-like cellular automata is presented. The proposed perspective studies some multifractal and informational properties of Boolean functions behind these rules. Results from this approach challenge the traditional argument about the simplicity of Lifelike rules.
Hidden complexity in Life-like rules
Miguel Melgarejo, Marco Alzate, and Nelson Obregon
Phys. Rev. E 100, 052133
Source: journals.aps.org
