Module:Emergence

Complex Systems Summer School 2011 Modules Home Schedule Concepts: Nonlinearity Networks Computation Robustness Evolution Complexity Emergence Machine Learning

Organized by Simon DeDeo and James O'Dwyer

Readings

Simon DeDeo

Some influential views on emergence

• "More is Different" (P.W. Anderson)
• The Calculi of Emergence & Computation at the Onset of Chaos (J. Crutchfield, et al.)
• Weak Emergence (M. Bedau)

Background concepts, tools and techniques

Many different fields invent similar tools to study emergent phenomena; browse through these below as you like, following in greater depth those that fit your skill set and interests.

• Scaling, Universality, and Renormalization: Three pillars of modern critical phenomena (E. Stanley; physics-centric, but not too painful.)
• Effective Field Theories, Reductionism and Scientific Explanation (S. Hartmann; a philosopher of science looks in detail at the methods of Effective Field Theories in Quantum Fields, a case study for many of the concepts that will appear during the module.)
• Stanford Encyclopedia entry on Supervenience (a useful concept to keep in mind when thinking about higher-level, or emergent, properties in a system.)
• Levels of Selection: An Alternative to Individualism in the Biological and Social Sciences (David Sloan Wilson; a nice example of the importance of levels thinking, and how aggregate properties and laws arise.)

Useful, but not directly related

• Information Theory and Statistical Mechanics (E.T. Jaynes; technical paper. The foundation of Maximum Entropy methods, that show how to extend thermodynamic analogies to non-physical systems and inference problems.)

Iain Couzin

(Content from the 2009/2010 Wikis)

• Complexity. An Informative Itinerary
• Collective Cognition in Animal Groups
• Collective Motion and Cannibalism in Locust Migratory Bands
• Collective Minds
• Effective Leadership and Decision-Making in Animal Groups on the Move