Course Readings

Introduction (1 week)
- Mitchell preface, Ch1, Ch 14 (p 209-212 only)
- Hall and Day Revisiting the limits to growth
- P. J. Denning, "Computing is a natural science"
- Optional: Barnosky et al. Approaching a state shift in Earth's biosphere
- MatlaB Tutorial. Download software from here.
Modeling Case Studies (2 weeks)
- Aug. 28: Mitchell, Ch. 15-16
- Aug. 30: Mitchell, Ch. 10
- Sept. 4: Mitchell, Ch. 9
- Sept. 6, Mithcell Ch. 2
Cellular automata (2 weeks)
- Sept. 11 - 13: Review: Mitchell Ch. 10
- Sept. 11 - 13: Wolfram A New Kind of Science Ch. 8 (available from here)
- Sept. 18 - 20: Axelrod Agent-bsaed modeling as a bridge between disciplines
- OPTIONAL: Specifying and sustaining pigmentation patterns in domestic and wild cats
- Interesting videos about modeling plant growth:
  - Part 1
  - Part 2
  - Part 3
Simulation underpinnings (1 week)
- Sept. 24 - 27: TO BE ANNOUNCED
Data analysis and scaling laws (3 weeks)
- Oct. 2 - 4: Review: Mitchell Ch. 15-17
- Oct. 2 - 4: Newman Ch. 8
- Oct. 2 - 8: OPTIONAL "Leverage causes fat tails and clustered volatility"
- Oct. 9 - 16: OPTIONAL: Power Law Distributions in Empirical Data Clauset, et al. (with Matlab code)
Predator/Prey Models and Nonlinear Dynamics (1 weeks)
- Oct. 30: Review Mitchell Ch. 2
- Oct. 30: G. Flake The Computational Beauty of Nature Ch. 12
- Oct. 30: Newman, Ch. 17 pp. 627 - 641
Genetic Algorithms and Optimization methods (2 weeks)
- Nov. 6: Mitchell Ch. 5, 6, Review 9, 18
- Nov. 8: G. Flake The Computational Beauty of Nature Ch. 20
Game Theory (1 week)
- Nov. 20: Mitchell Ch. 14 (213-224)
- Nov. 27: G. Flake The Computational Beauty of Nature Ch. 17
Bayesian Networks (1 week)
- Dec. 4 - 6: T. Mitchell Machine Learning Ch. 6, McGraw Hill, 1997.
- Dec. 4 - 6: E. Charniak "Bayesian Networks Without Tears"
Review and catchup (1 week)
- H. Simon ”The architecture of complexity”