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Difference between revisions of "CSSS 2006 Beijing-Readings"

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Herbert Gintis, [[Media:Unity-bbs.pdf|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. The rest will be based on various papers available from his[[http://www-unix.oit.umass.edu/~gintis web site.]]
 
Herbert Gintis, [[Media:Unity-bbs.pdf|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. The rest will be based on various papers available from his[[http://www-unix.oit.umass.edu/~gintis web site.]]
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'''Dave Feldman'''
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[[Media:Final.remarks.pdf|Summary and Final Remarks]]
  
 
== General Background ==
 
== General Background ==

Latest revision as of 20:29, 29 August 2006

CSSS 2006 Beijing



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

Part Two- Villages and the Emergernce of Tribal Alliance Systems

Part Three- Raising Civilizations


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.

Further reading


Cosma Shalizi

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.

See also:Methods and Techniques of Complex Systems Science: An Overview, nlin.AO/0307015.

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 Two

Li Shuzhuo & Marcus W.Feldman July 17, Morning

Population dynamics introduction.

Marcus W.Feldman & Li Shuzhuo July 17, Afternoon

Rural-urban Migration in China Social Networks and Socio-demography.

Marcus W.Feldman July 18, Morning

Niche construction A new dimension for biological and cultural evolution.


Jing Han lecture notes 1, 2, 3.

About Soft-control.


Jim Crutchfield

Background for lecture two:

Week Three

Hao Bai-lin


Lee Altenberg

Lecture Slides


Background Reading

  • 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. , 1994. The Schema Theorem and Price's Theorem delves into the claims about schema processing as the source of power in genetic algorithms, and recasts the Schema Theorem (Holland 1975) by using Price's Theorem (1970). It is shown that the Schema Theorem says nothing about a GA's power, but a modification with a different measurement function produces a theorem about evolvability that is a local measure of GA power. The concept of rugged landscapes is also deconstructed in terms of operator-defined distance.
  • Erik van Nimwegen, James P. Crutchfield, and Martijn Huynen Neutral Evolution of Mutational Robustness. Proceedings of the National Academy of Science U.S.A. 96:9716-9720 (1999).

Additional Reading

Links Evolutionary Art at Electric Sheep


William S-Y. Wang & James W. Minett, July 24 & 25, 10:30-11:45

Notes to Lectures 1 and 2.

Bibliography to Lectures 1 and 2.


William S-Y. Wang & James W. Minett, July 26, 10:30-11:45

Introduction to Lectures 3 to 5.

Bibliography to Lectures 3 to 5.

Lecture 3: Modeling the ontogenetic emergence of language using recurrent neural networks.


William S-Y. Wang & James W. Minett, July 27, 10:30-11:45

Lecture 4: Modeling the phylogenetic emergence of language using agent-based modeling.


William S-Y. Wang & James W. Minett, July 28, 10:30-11:45

Lecture 5: Modeling language competition and death using differential equations and agent-based modeling.


Van Savage

Lecture 1

Week Four

Michelle Girvan

Lecture 1 Lecture 2


Herbert 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. The rest will be based on various papers available from his[web site.]


Dave Feldman

Summary and Final Remarks

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.