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===Lecture Notes===
===Lecture Notes===
* [[Media:Feldman_1.pdf|Introduction]]
 
<!--* [[Media:Feldman_2.pdf|Dynamical Systems and Chaos]]
* [[Media:Feldman.china.08.pdf | Some Foundations in Complex Systems: Entropy, Information, Computation, and Complexity]]. Complete set of slides from all five lectures.
* [[Media:Feldman_3.pdf|Introduction to Chaos: Part II]]
 
* [[Media:Feldman_4.pdf|Information Theory]]
* [[Media:Feldman_5.pdf|Information Theory: Part II, Applications to Stochastic Processes]]
* [[Media:Feldman_12.pdf|Extensions to Shannon Entropy]]
* [[Media:Feldman_6.pdf|A (Mostly) Informal Introduction to Computation Theory]]
* [[Media:Feldman_7.pdf|An Informal Introduction to Computability and Computational Complexity]]
* [[Media:Feldman_8.pdf|An Introduction to Computational Mechanics]]
* [[Media:Feldman_9.pdf|Some Thoughts on Complexity Measures]]
* [[Media:Feldman_11.pdf|Thoughts on the Subjectivity of Complexity]]
* [[Media:Feldman_10.pdf|Conclusion]]-->


===Additional Reading===
===Additional Reading===


====General Complex Systems====
* David Feldman, Carl McTague, James Crutchfield, [http://arxiv.org/abs/0806.4789 The Organization of Intrinsic Computation: Complexity-Entropy Diagrams and the Diversity of Natural Information Processing].  An examination of the relationships between complexity and entropy for many different model systems.  I covered this material on the last day of my lectures.
 
* James Crutchfield, [[Media:Crutchfield.order.and.chaos.pdf|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.
* James Crutchfield, [[Media:Crutchfield.order.and.chaos.pdf|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.
<!--* [http://cob.jmu.edu/rosserjb/ J.B. Rosser], [http://cob.jmu.edu/rosserjb/GENERIC.CPX.doc 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. [http://ideas.repec.org/a/aea/jecper/v13y1999i4p169-192.html pdf format, for AEA members].-->
<!--* [http://cob.jmu.edu/rosserjb/ J.B. Rosser], [http://cob.jmu.edu/rosserjb/GENERIC.CPX.doc 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. [http://ideas.repec.org/a/aea/jecper/v13y1999i4p169-192.html pdf format, for AEA members].-->


* Cosma Shalizi, [[Media:Shalizi.overview.pdf|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 [http://arxiv.org/abs/nlin.AO/0307015 here].
* Cosma Shalizi, [[Media:Shalizi.overview.pdf|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 [http://arxiv.org/abs/nlin.AO/0307015 here].


====Entropy Rate, Excess Entropy====
*J.P. Crutchfield and D. P. Feldman Regularities Unseen, Randomness Observed: Levels of Entropy Convergence.  Chaos, 2003. 15: 25-54. 2003. [http://arxiv.org/abs/cond-mat/0102181 cond-mat:0102181].  This is a long paper discussing the entropy rate and excess entropy and including many different examples. 


*J.P. Crutchfield and D. P. Feldman Regularities Unseen, Randomness Observed: Levels of Entropy Convergence.  Chaos, 2003. 15: 25-54. 2003. [http://arxiv.org/abs/cond-mat/0102181 cond-mat:0102181].  This is a long paper discussing the entropy rate and excess entropy and including many different examples. 
* 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. [http://arxiv.org/abs/cs.LG/0406011 cs.LG/0406011]


<!--*[[Media:Comp.ent.diagrams.4.pdf|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 DavisAdditional info on some of the ideas from Lecture 4.-->
* K. L. Klinkner, C. R. Shalizi and M. F. Camperi, "Measuring Shared Information and Coordinated Activity in Neuronal Networks", <cite>Advances in Neural Information Processing Systems 18</cite> (NIPS 2005), pp. 667--674Using CSSR to measure information sharing in networks (not just neural ones)[http://arxiv.org/abs/q-bio.NC/0506009 q-bio.NC/0506009]


==Miguel Fuentes==


====Computational Mechanics====
[[Media:FuentesTalk.pdf | Laplace's Deterministic Paradise Lost ]]


* 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. [http://arxiv.org/abs/cs.LG/0406011 cs.LG/0406011]
==Hao Bailin==
===Lecture Notes===


* K. L. Klinkner, C. R. Shalizi and M. F. Camperi, "Measuring Shared Information and Coordinated Activity in Neuronal Networks", <cite>Advances in Neural Information Processing Systems 18</cite> (NIPS 2005), pp. 667--674.  Using CSSR to measure information sharing in networks (not just neural ones).  [http://arxiv.org/abs/q-bio.NC/0506009 q-bio.NC/0506009]
[[Media:ChineseCharacters.ppt| A Brief Introduction to Written Chinese]]


==Will Tracy==
==Will Tracy==
===Lecture Notes===
===Lecture Notes===


*[[Media:Will_Tracy_Lecture_1.ppt | Computational Complexity in the Social Sciences I]]
*[[Media:Will_Tracy_Lecture_2.ppt | Computational Complexity in the Social Sciences II]]


===Additional Reading===
===Additional Reading===
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===Lecture Notes===
===Lecture Notes===


Introduction to SFI: Monday, July 9
<!--Introduction to SFI: Monday, July 9
* [[Media:Wilkins_CSSS_2007_Intro.pdf|Introduction to SFI]]
* [[Media:Wilkins_CSSS_2007_Intro.pdf|Introduction to SFI]]-->


Lecture 1: Monday, July 9
Lecture 1: Monday, June 30
* [[Media:Wilkins_7-9.pdf|Introduction to Coalescent Theory]]
* [[Media:Wilkins_CSSS_2008_1.ppt|Adaptationism and the Adaptive Landscape]]


Lecture 2: Wednesday, July 11
Lecture 2: Wednesday, July 2
* [[Media:Wilkins_7-11.pdf|Adaptationism and the Adaptive Landscape]]
* [[Media:Wilkins_CSSS_BJ_2008_2.ppt | Geneologies I: Introduction to Coalescent Theory]]


Lecture 3: Friday, July 13
<!--Lecture 3: Friday, July 13
* [[Media:Wilkins_CSSS_2007_3.pdf|Statistical Inference in Complex Systems: Approximate Bayesian Computation]]
* [[Media:Wilkins_CSSS_2007_3.pdf|Statistical Inference in Complex Systems: Approximate Bayesian Computation]]-->


===Additional Reading===
===Additional Reading===
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===Lecture Notes===
===Lecture Notes===
*  
*[[Media:CSSS08_States.pdf|Modeling Early Civilizations: First Steps]].


===Additional Reading===
===Additional Reading===
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*[[Media:Digitizing_Devpmnt.pdf|Digitizing 'Development']] Stefan Helmreich
*[[Media:Digitizing_Devpmnt.pdf|Digitizing 'Development']] Stefan Helmreich
*[[Media:Foucault.pdf|Foucault and the Water Temples]] Steve Lansing
*[[Media:Foucault.pdf|Foucault and the Water Temples]] Steve Lansing
*[[Media:Wilkinson_MASS.doc|Urbanization Within a Dynamic Environment]] T.J. Wilkinson, J.H. Christiansen, J. Ur, M. Widell, and M. Altaweel
*[[Media:Wilkinson_MASS_Figs.pdf|Figures to Accompany "Urbanization Within a Dynamic Environment"]] T.J. Wilkinson, J.H. Christiansen, J. Ur, M. Widell, and M. Altaweel
==Richard Callahan==
===Download SIENA===
* Go to http://stat.gamma.rug.nl/stocnet/ to download StOCHNET, the Graphical User Interface that houses SIENA. StOCHNET comes built in with last year's version of SIENA. Download the .zip file for version 1.8 and run the executable.
* There's also a brand-new version of SIENA that came out on Monday that you can download from http://stat.gamma.rug.nl/siena.html. You should just have to switch the executables for SIENA that unpack with StOCHNET with these newer ones. Apologies but I haven't yet done this myself, so I can't verify that the process works as it should.
===Data===
* Looks like I couldn't upload a .zip file to the Wiki, so you can find the data for this workshop on my Web site at http://students.washington.edu/rjcal/links.shtml.
===Lecture Notes===
* [[Media:Callahan_SIENA_2008_presentation.ppt|Introduction to Dynamic Social Network Analysis with SIENA]]
* [[Media:Survival_Mandarin.ppt|Sample Mandarin Dialogues to Practice!]] Most of these slides came from Will Tracy's talk last year.
===Additional Reading===
* Link to http://stat.gamma.rug.nl/siena.html and click on 'Literature'. Also useful (but copyrighted, so you have to get it from your library unfortunately): Robins, Snijders, Wang, Handcock and Pattison, "Recent Developments in Exponential Random Graph Models for Social Networks", Social Networks 29(2007): 192-215.

Latest revision as of 02:46, 8 July 2008

CSSS 2008 Beijing


Dave Feldman

Lecture Notes


Additional Reading

  • 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.
  • 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.
  • 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.
  • 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. 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

Miguel Fuentes

Laplace's Deterministic Paradise Lost

Hao Bailin

Lecture Notes

A Brief Introduction to Written Chinese

Will Tracy

Lecture Notes

Additional Reading

Jon Wilkins

Lecture Notes

Lecture 1: Monday, June 30

Lecture 2: Wednesday, July 2


Additional Reading

Coalescent Theory:

Here are two different introductions to coalescent theory. One is a review article written by Magnus Nordborg:

The other is a chapter from John Wakeley's book called Coalescent Theory

If you are interesed in learning a lot more about the subject, I recommend the rest of the book as well


Genomic Imprinting:

Here are a couple of review articles that talk about the evolution of genomic imprinting

Here are some modeling papers on imprinting. The first two are the models that I used as an example in Wednesday's lecture

These are some papers that look at what happens when there are more than two "players" or "genetic factions" that are co-evolving

Also, here is a paper that talks about how the level of analysis in evolutionary problems affects how you perceive the role of natural selection in evolution It is now out it the Blackwell Companion to the Philosophy of Biology. It is the article entry on "Adaptationism" I don't have the final PDF with me, though, so I have attached the final draft that we sent to the publishers. I suspect that it is similar, though.

  • Adaptationism Godfrey Smith and Wilkins, Blackwell Companion to the Philosophy of Biology, 1997


Approximate Bayesian Computation

Here are a few papers that describe the basic ideas of Approximate Bayesian Computation. In these papers, the applications are specifically population genetic. One warning: the techniques used in these papers to deal with the issues of correlations among statistics, etc. are completely ad hoc. The procedure that I outlined on Friday is somewhat less ad hoc. Soon, I hope to post something that provides a written description of what I talked about. Conceivably, even some code to implement these steps.

Henry Wright

Lecture Notes

Additional Reading

Foragers and the Emergence of Agriculture

Villages and the Emergernce of Tribal Alliance Systems

Raising Civilizations

Richard Callahan

Download SIENA

  • Go to http://stat.gamma.rug.nl/stocnet/ to download StOCHNET, the Graphical User Interface that houses SIENA. StOCHNET comes built in with last year's version of SIENA. Download the .zip file for version 1.8 and run the executable.
  • There's also a brand-new version of SIENA that came out on Monday that you can download from http://stat.gamma.rug.nl/siena.html. You should just have to switch the executables for SIENA that unpack with StOCHNET with these newer ones. Apologies but I haven't yet done this myself, so I can't verify that the process works as it should.

Data

Lecture Notes

Additional Reading

  • Link to http://stat.gamma.rug.nl/siena.html and click on 'Literature'. Also useful (but copyrighted, so you have to get it from your library unfortunately): Robins, Snijders, Wang, Handcock and Pattison, "Recent Developments in Exponential Random Graph Models for Social Networks", Social Networks 29(2007): 192-215.