Topic: complex systems

Eric Beinhocker and Nick Hanauer present Market Humanism as a proposed framework for an economy centred on human flourishing. They interpret the period since the financial crisis as a gap between economic paradigms, with consequences for democracy, climate action and responses to artificial intelligence. Drawing on economics, philosophy, behavioural and social sciences, complex systems, evolutionary theory and computer science, they outline the proposed framework and its implications for policy and business. The discussion considers how it could alter politics and public narratives, and the p

A rich data representation that finds wide application in industry and research is the so-called knowledge graph - a graph-based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context-aware predictions in these information-packed environments.

Physics offers countless examples for which theoretical predictions are astonishingly powerful. But it’s hard to imagine a similar precision in complex systems where the number and interdependencies between components simply prohibits a first-principles approach, look no further than the challenge of the billions of neurons and trillions of connections within our own brains. In such settings how do we even identify the important theoretical questions? We describe a systems-scale perspective in which we integrate information theory, dynamical systems and statistical physics to extract understan