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

Practical

For the upcoming Emergence module, there will be two options at the practical Tuesday afternoon:

1. for those who have group projects that they are excited about, James and I will join in discussions about how concepts and tools from the lectures can be usefully applied.

2. for those who want focused practice, we will have a guided practical, outlined on the worksheet, on topological defects and the dynamics of phase transitions as applied to physical, biological and social systems.

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; I disagree with MB, but his view is popular and held by many respectable people.)

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