Module:Complexity

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

Organized by Jim Crutchfield

Background

• T. Cover and J.Thomas, Elements of Information Theory, Wiley, Second Edition (2006) Chapters 1 - 7.
• M. Li and P.M.B.Vitanyi, An Introduction to Kolmogorov Complexity and its Applications , Springer, New York (1993).
• J. P. Crutchfield and D. P. Feldman, “Regularities Unseen, Randomness Observed: Levels of Entropy Convergence”,CHAOS 13:1 (2003) 25-54.

Lecture Notes

• Thursday
  1. Processes and Their Models: Complexity Lecture 1A (PDF)
  2. Information Theory: Complexity Lecture 1B (PDF)
  3. Information in Processes: Complexity Lecture 1C (PDF)
  4. Memory in Processes: Complexity Lecture 1D (PDF)
• Friday
  1. The Learning Channel: Complexity Lecture 2A (PDF)
  2. Causal Models: Complexity Lecture 2B (PDF)
  3. Measures of Complexity: Complexity Lecture 2C (PDF)
  4. Applications: Complexity Lecture 2D (PDF)

Ryan's talks

1. Anatomy of an Observation
2. Length Scales in Complex Time Series

Readings

The Calculi of Emergence

Pattern Discovery and Computational Mechanics

Many Roads to Synchrony: Natural Time Scales and Their Algorithms

Synchronization and Control in Intrinsic and Designed Computation: An Information-Theoretic Analysis of Competing Models of Stochastic Computation

Information Accessibility and Cryptic Processes

Prediction, Retrodiction, and The Amount of Information Stored in the Present

The Organization of Intrinsic Computation: Complexity-Entropy Diagrams and the Diversity of Natural Information Processing

Anatomy of a Bit

Online Labs

CMPy Notebook