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 1 (PDF)
  2. Information Theory: Complexity Lecture 1 (PDF)
  3. Information in Processes: Complexity Lecture 1 (PDF)
  4. Memory in Processes: Complexity Lecture 1 (PDF)
• Friday
  1. The Learning Channel: Complexity Lecture 2 (PDF)
  2. Causal Models: Complexity Lecture 2 (PDF)
  3. Measures of Complexity: Complexity Lecture 2 (PDF)
  4. Applications: Complexity Lecture 2 (PDF)

Readings

The Calculi of Emergence

Pattern Discovery and Computational Mechanics

Many Roads to Synchrony: Natural Time Scales and Their Algorithms

[hhttp://arxiv.org/abs/1007.5354 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

Links

CMPy Notebook