Month: August 2020

Rise of the Self-Replicators – Early Visions of Machines, AI and Robots That Can Reproduce and Evolve

Taylor, Tim, Dorin, Alan

 

Is it possible to design robots and other machines that can reproduce and evolve? And, if so, what are the implications: for the machines, for ourselves, for our environment, and for the future of life on Earth and elsewhere?
In this book the authors provide a chronological survey and comprehensive archive of the early history of thought about machine self-reproduction and evolution. They discuss contributions from philosophy, science fiction, science and engineering, and uncover many examples that have never been discussed in the Artificial Intelligence and Artificial Life literature before now. In the final chapter they provide a synthesis of the concepts discussed, offer their views on the field’s future directions, and call for a broad community discussion about the significant implications of intelligent evolving machines.
The book will be of interest to general readers, and a valuable resource for researchers, practitioners, and historians engaged with ideas in artificial intelligence, artificial life, robotics, and evolutionary computing.

Source: www.springer.com

CCS2020 Conference on Complex Systems 2020, online 7-12 December.

CCS2020 is the flagship conference promoted by the Complex Systems Society. It brings under one umbrella a wide variety of leading researchers, practitioners and stakeholders with a direct interest in Complex Systems, from Physics to Computer Science, Biology, Social Sciences, Economics, and Technological and Communication Networks, among others.

 

Call for Satellites deadline: September 20th

Abstract submission deadline: October 10th

 

Source: ccs2020.web.auth.gr

Classical information theory of networks

Filippo Radicchi, Dmitri Krioukov, Harrison Hartle and Ginestra Bianconi

Journal of Physics: Complexity, Volume 1, Number 2

 

Existing information-theoretic frameworks based on maximum entropy network ensembles are not able to explain the emergence of heterogeneity in complex networks. Here, we fill this gap of knowledge by developing a classical framework for networks based on finding an optimal trade-off between the information content of a compressed representation of the ensemble and the information content of the actual network ensemble. We introduce a novel classical network ensemble satisfying a set of soft constraints and we find the optimal distribution of the constraints for this ensemble. We show that for the classical network ensemble in which the only constraints are the expected degrees a power-law degree distribution is optimal. Also, we study spatially embedded networks finding that the interactions between nodes naturally lead to non-uniform spread of nodes in the embedding space, leading in some cases to a fractal distribution of nodes. This result is consistent with the so called `blessing of non-uniformity’ of data, i.e. the fact that real world data typically do not obey uniform distributions. The pertinent features of real-world air transportation networks are well described by the proposed framework.

 

Source: iopscience.iop.org

GDP Is the Wrong Tool for Measuring What Matters

Joseph E. Stiglitz

 

  • Gross domestic product (GDP) is almost universally used to gauge how well a society is doing. In fact, it is a measure of market activity—no more.
  • The Great Recession of 2008–2009 highlighted the need for better ways to measure the well-being of an economy and society, as well as its sustainability—whether or not good times can last.
  • Over the past decade leading scholars have devised a broad set of measures to help steer societies toward the futures their citizens desire. Several countries are embedding these “dashboard” indicators into their decision-making processes.

Source: www.scientificamerican.com