CSSS 2006 Beijing-Readings

CSSS 2006 Beijing Home Faculty Participants Participant´s Photos Schedule Public Lectures Content Final Details Readings Survey Feedback Week 1 Feedback Week 2 Feedback Week 3 Feedback Week 4 Forum Projects Program Info Themes Poster Final Papers

Below are some readings that can provide some background for some of the lectures and/or that you can read after the lecturers to pursue some ideas further.

Readings Associated with Particular Lecturers

Week One

Andreas Wagner

Genome-scale Biological Networks. These are the slides that Andreas will use for his lectures. We will make hard copies available at the CSSS.

Henry Wright

This file introduces you to the web resources for Part 1 of Henry Wright's Presentation at the 2006 CSSS in Beijing. Here are some other readings associated with Henry Wright's talks:

Part One- Foragers and the Emergence of Agriculture

• Brief Syllabus of Sources on the “Forager” Project
• PowerPoint presentation of Part 1
• Boundary Conditions for Paleolithic Social Systems: A Simultaion Approach. Martin Wobst.
• Archaological Systems Theory and Early Mesoamerica, Kent V. Flannery. In Anthropological Archaeology in the Americas. The Anthropological Society of Washington. 1968.
• The Research Problem, Kent V. Flannery. In Guila Naquitz: Archaic Foraging and Early Agriculture in Oaxaca, Mexico, Ken V. Flannery, ed.
• Guila Naquitz in Spacial, Temporal, and Cultural Context, Kent V. Flannery. In Guila Naquitz: Archaic Foraging and Early Agriculture in Oaxaca, Mexico, Ken V. Flannery, ed..
• The Physical Environment of the Guila Naquitz Cave Group, Kirkby, M. J., A. V. Whyte, and K. V. Flannery. In Guila Naquitz: Archaic Foraging and Early Agriculture in Oaxaca, Mexico, Ken V. Flannery, ed..
• The Modeling of Foraging Strategy: An Introduction to Part IV, Robert Reynolds. In Guila Naquitz: Archaic Foraging and Early Agriculture in Oaxaca, Mexico, Kent V. Flannery, ed.
• Jared Diamond's Overview of the Emergence of Food Production

Part Two- Villages and the Emergernce of Tribal Alliance Systems

• Brief Syllabus of Sources on the “Village” Project
• PowerPoint presentation of Part 2
• Simulating Ancient Societies Kohler, T. A., G.J. Gumerman and R.G. Reynolds
• Agent-Based Modeling of Prehistoric Settlement Systems in the Northern American Southwest Kohler, T. A., C. R. Van West, E. P. Carr and C. G. Langton
• Cultural Algorithms: A Tutorial Robert G. Reynolds
• A Multi-Agent Simulation Using Cultural Algorithms: The Effect of Culture on the Resilience of Social Systems Kobti, Z., R. G. Reynolds, and T. A. Kohler
• The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region Reynolds, R. G., T. A. Kohler and Z. Kobti
• The Effect ofKinship Cooperation Learning Stategy and culture on the Resilience of Social Systems in the Village Mulit-Agent Simulation Kobti, Z., R. G. Reynolds, and T. A. Kohler
• Agent-Based Modeling of Cultural Change in Swarm Using Cultural Algorithms Kobti, Z., R. G. Reynolds, and T. A. Kohler
• Unraveling Ancient Mysteries: Reimagining the Past Using Evolutionary Computation in a Complex Gaming Environment Reynolds, R. G., Z. Kobti, T. A. Kohler, and L. Y. L. Yap

Part Three- Raising Civilizations

• Brief Syllabus of Sources on the “States” Project
• PowerPoint presentation of Part 3
• A Theory of the Origin of the State Robert L. Carneiro
• Recent Research on the Origin of the State Henry T. Wright
• The Changing Organization of Uruk Administration on the Susiana Plain Gregory A. Johnson. In The Archaeology of Western Iran, Frank Hole, ed.
• Uruk States in Southwestern Iran Henry T. Wright. In Archaic States, Gary M. Feinman and Joyce Marcus, eds.
• Cultural Action in the Uruk World Henry T. Wright. In Uruk Mesopotamia & Its Neighbors, Mitchell S. Rothman, ed.
• Settlement Patterns, Chiefdom Variability, and the Development of Early States in North China Li Liu
• Regional survey and the development of complex societies in southeastern Shandong, China Underhill, A. P., G. M. Feinman, L. M. Nicholas, G. Bennett, H. Fang, F. Luan, H. Yu and F. Cai
• control strategies and polity competition in the lower Yi-Luo Valley, North China Yun Kuen Lee
• System-dependent Selection, Ecological Feedback and the Emergence of Functional Struction in Ecosystems Lansing, S. J., J. N. Kremer, and B. B. Smuts
• Digitizing 'Development' Stefan Helmreich
• Foucault and the Water Temples Steve Lansing

Dave Feldman

Annotated bibliography to accompany Dave's lectures. In addition to references specific to the lecture topics, there are also a number of general complex systems references.

• Lecture 1: Introduction to Chaos. Introductory Comments, Part I, Part II
• Lecture 2: Information Theory Part I, Part II
• Lecture 3: Computation Theory. Automata and Computation Theory, Computability and Computational Complexity
• Lecture 4: Measures of Complexity. Computational Mechanics, Conclusion

Further reading

• J.P. Crutchfield and D. P. Feldman Regularities Unseen, Randomness Observed: Levels of Entropy Convergence. Chaos, 2003. 15: 25-54. 2003. cond-mat:0102181. This is a long paper discussing the entropy rate and excess entropy and including many different examples.
• Complexity Entropy Diagrams: Exploring the Relationships between Complexity and Randomness. Talk given in February 2006 at the Center for Computational Science and Engineering at UC Davis. Additional info on some of the ideas from Lecture 4.

Cosma Shalizi

• Lecture 1: Power Laws, What They Mean, How to Tell If You Have One

M. E. J. Newman, Power laws, Pareto distributions and Zipf's law, Contemporary Physics 46, 323-351 (2005). An excellent paper. Good background for Cosma's lecture on power laws.

• Lecture 2: Statistical Inference for Complex Systems Models

• Lecture 3: Optimal Prediction, Model Discovery and Self-Organization

C. R. Shalizi and K. L. Klinkner, "Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences", Uncertainty in Artificial Intelligence: Proceedings of the Twentieth Conference (UAI 2004), pp. 504--511. Best description of the CSSR algorithm; helpful for third lecture. cs.LG/0406011

K. L. Klinkner, C. R. Shalizi and M. F. Camperi, "Measuring Shared Information and Coordinated Activity in Neuronal Networks", Advances in Neural Information Processing Systems 18 (NIPS 2005), pp. 667--674. Using CSSR to measure information sharing in networks (not just neural ones). q-bio.NC/0506009

Week Three

Lee Altenberg

• Altenberg, L. , 2004. Open Problems in the Spectral Analysis of Evolutionary Dynamics presents a mathematical framework for evolutionary optimization and some of its unsolved problems.
• Altenberg, L. , 2004. Modularity in Evolution: Some Low Level Questions deconstructs the concept of modularity in terms of spaces of variation, and discusses properties needed for modularity to enhance evolvability.

Week Four

Herb Gintis

Herbert Gintis, A Framework for the Unification of the Behavioral Sciences. Behavioral and Brain Sciences, forthcoming 2006. Parts of Herb's lectures will be based on this paper.

General Background

James Crutchfield, What Lies between Order and Chaos?, in Art and Complexity, J. Casti, editor, Oxford University Press (2002). An interesting, non-technical essay discussing how new patterns are discovered, and how complexity arises from the interplay between order and chaos. This is an excellent introduction to the notions of complexity and emergence, and history of one strand of the study of complex systems.

J.B. Rosser, On the Complexities of Complex Economic Dynamics. Journal of Economic Perspectives. 13:169-192. 1999. I've only read about half of this. It strikes me as a thorough, even-handed review of the applications of "complexity theory" to economics. Presents good spectrum of views, from those who think complexity is mostly hype, to those who believe it has contributed significant new understandings. Contains around 125 references. pdf format, for AEA members.

Cosma Shalizi, Methods and Techniques of Complex Systems Science: An Overview. Chapter 1 (pp. 33--114) in Thomas S. Deisboeck and J. Yasha Kresh (eds.), Complex Systems Science in Biomedicine (New York: Springer, 2006.) This is an excellent, thorough review of the "field" -- to the extent that there is such a thing -- of complex systems. Covers many tools: statistical learning and model selection; time series analysis; cellular automata; agent-based models; the evaluation of complex-systems models; information theory; and ways of measuring complexity. Contains over 250 references. Also available here.