Resources on Complexity including all of the previous readings
Recommended Readings
General
Cosma's Research Notebooks: http://www.cscs.umich.edu/~crshalizi/notebooks/
What is complexity?
Edgar Morin: A partial introduction" by A. Montuori, California Institute of Integral Studies http://www.ciis.edu/faculty/articles/montuori/Morin_Montuori.pdf
Books on complexity
John Holland, Hidden Order
Gary Williams Flake, The computational beauty of nature
Economics
John Miller and Scott Page, Complex Adaptive Systems
Eric D. Beinhocker, Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics
Yochai Benkler, The Wealth of Networks: How Social Production Transforms Markets and Freedom
Joshua M. Epstein and Robert L. Axtell, Growing Artificial Societies: Social Science from the Bottom Up
Peter Turchin, Historical Dynamics: Why States Rise and Fall
Brian Arthur, Increasing Returns and Path Dependence in the Economy
Philip W. Anderson, Kenneth Arrow, David Pines (Editors), The Economy As An Evolving Complex System
Lawrence E. Blume, Steven N. Durlauf (Editors), The Economy As an Evolving Complex System, III
Entropy
"A simple introduction to Maximum Entropy Models for Natural Language Processing", Adwait Ratnaparkhi, May 1997, Institute for Research in Cognitive Science Technical Report, http://tiger.towson.edu/users/dknopp1/simpl-intro-to-maxent
Maximum entropy exchange equilibrium, Duncan K. Foley, May 2002, Work in Progress, http://homepage.newschool.edu/~foleyd/maxentexeq.pdf
The backwards arrow of time of the Coherent Bayesian Statistical Mechanics, Cosma Shalizi, November, 2004, http://arxiv.org/PS_cache/cond-mat/pdf/0410/0410063v2.pdf
John Whitfield, Complex systems: Order out of chaos, Nature, Volume 436 Number 7053, p905, http://www.nature.com/nature/journal/v436/n7053/full/436905a.html
H. Van Dyke Parunak, Sven Brueckner: Entropy and self-organization in multi-agent systems. Agents 2001: 124-130, http://citeseer.ist.psu.edu/378331.html
"Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states", Roderick Dewar, 2003, J. Phys. A: Math. Gen., v36 p631-641, http://www.iop.org/EJ/abstract/0305-4470/36/3/303/
Diversity
"Groups of diverse problem solvers can outperform groups of high-ability problem solvers", Lu Hong and Scott Page, 2004, Proceedings of the National Academy of Sciences, v101, n46, p16385-16389, http://www.cscs.umich.edu/~spage/pnas.pdf
Graphical Models
"Introduction to Inference for Bayesian Networks", Robert Cowell, 1998
http://ccl.northwestern.edu/~wrand/nrg/intro_bayesian_nets.pdf
"Inferring Cellular Networks Using Probabilistic Graphical Models", Nir Friedman, Science, 2004, http://www.sciencemag.org/cgi/content/abstract/303/5659/799
"An Introduction to Variational Methods for Graphical Modeling", Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola and Lawrence K. Saul, Machine Learning, Volume 37, Number 2 / November, 1999, 183-233 (I recommend through page 198), http://www.springerlink.com/index/N811M25287935571.pdf
Information Theory
"Information and Entropy Econometrics--An Editor's View", Amos Golan, Journal of Econometris, 2002, Only read pages 1-16, v107, iss. 1-2, http://www.american.edu/academic.depts/cas/econ/faculty/golan/infoentropy.pdf
"Induction of Decision Trees", J. R. Quinlan, Machine Learning, v1n1, March, 1986, p81-106, http://www.cs.toronto.edu/~roweis/csc2515/readings/quinlan.pdf
Rugged Landscapes
Kirkpatrick, Gelatt, and Vecchi, Optimization by Simulated Annealing, Science 220, 671-680 (1983).
http://amaral.northwestern.edu/roger/SA.pdf
Fleming and Sorenson, Technology as a complex adaptive system: evidence from patent data, Research Policy v30 (2001) p1019-1039 http://ccl.northwestern.edu/~wrand/nrg/fleming.pdf
Kauffman and Levin, Towards a general theory of adaptive walks on rugged landscapes, J. Theor. Biol 128, 11-45 (1987)
http://amaral.northwestern.edu/roger/NK.pdf (first page slightly cut at the bottom)
Optimization and Search
"A Genetic Algorithm Tutorial", Darrell Whitley, http://samizdat.mines.edu/ga_tutorial/ga_tutorial.ps
"Tabu Search: A Tutorial", Fred Glover, Interfaces; Jul/Aug90, Vol. 20 Issue 4, p74-94, http://leeds-faculty.colorado.edu/glover/TS%20-%20Interfaces.pdf
Nonlinear Dynamics
"Dynamic Pattern Formation: A Primer" J. A. Scott Kelso, Mingzhou Ding and Gregor Schoner (1993), p13-46 from "A Dynamic Systems Approach to Development" Edited by Linda B. Smith and Esther Thelen http://ccl.northwestern.edu/~wrand/nrg/kelso_etal_1993.pdf (p 13-27 our highly recommended)
"Parsing in a Dynamical System: An Attractor-based Account of the Interaction of Lexical and Structural Constraints in Sentence Processing" Whitney Tabor, Cornell Juliano and Michael K. Tanenhaus (1997), p211-271, Language and Cognitive Processes, v12 (2/3) http://taylorandfrancis.metapress.com/content/lcrx490d5r5mek6x/fulltext.pdf
Statistical Analysis
"The Future of Power-law Research", Michael Mitzenmacher, Internet Mathematics 2(4): 525-528 (only the first 4 pages), http://www.eecs.harvard.edu/~michaelm/postscripts/im2006a.pdf
"Superfamilies of designed and evolved networks", R Milo, S Itzkovitz, N Kashtan, R Levitt, S Shen-Orr, I Ayzenshtat, M Sheffer & U Alon. Science, 303:1538-42 (2004) http://www.weizmann.ac.il/mcb/UriAlon/Papers/Superfamilies_of_Evolved_and_Designed_Networks.pdf
"Modularity from fluctuations in random graphs and complex networks" Guimera, Sales-Pardo, Amaral. Phys. Rev. E 70, art. no. 025101, 1-4 (2004) http://amaral.northwestern.edu/Publications/Papers/Guimera-2004-Phys.Rev.E-70-025101.pdf
Game Theory
Nash, John (1950) "Equilibrium points in n-person games" Proceedings of the National Academy of the USA 36(1):48-49. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1063129
"An Introduction to Game Theory", p11-19, Martin J. Osborne, 2002, http://www.chass.utoronto.ca/~osborne/igt/nash.pdf
Evolutionary game theory. Current Biology, 1999. Karl Sigmund and Michael Nowak
http://www.ped.fas.harvard.edu/people/faculty/publications_nowak/CurBio99a.pdf
Patents and Networks
"Technology as a complex adaptive system: evidence from patent data", Lee Fleming and Olav Sorenson, Research Policy, v30, 2001, 1019-1039, http://www.people.hbs.edu/lfleming/RP2001.pdf
"A role-based ecology of technological change", Joel M. Podolny and Toby E. Stuart, American Journal of Sociology, v100n5, March 1995, p1224-60, http://web.ebscohost.com.turing.library.northwestern.edu/ehost/detail?vid=1&hid=7&sid=3fa354ac-82fd-4fa8-af36-bf4a51cb750d%40sessionmgr8
"Law and the science of networks: an overview and an application to the 'Patent Explosion'", Katherine J. Strandburg, Gabor Csardi, Jan Tobochnik, Peter Erdi, & Laszlo Zalanyi, Berkeley Technological Law Journal, v21n4, p1-70, http://works.bepress.com/katherine_strandburg/2/
Neural Modeling
For a broader perspective on single-neuron modeling, I recommend this review published last month in Science: Modeling single-neuron dynamics and computations: A balance of detail and abstraction http://www.sciencemag.org/cgi/content/full/sci;314/5796/80
For a more detailed mathematical treatment, I recommend this book chapter: Understanding neuronal dynamics by geometrical dissection of minimal models by A. Borisyuk and J. Rinzel http://www.cns.nyu.edu/~rinzel/compNeuro05/NeuroDynamics_AB_JR_Chapt.pdf
Land Use / Land Change
Rand, William, Brown, Daniel G., Page, Scott E., Riolo, Rick, Fernandez, Luis E., and Moira Zellner, Agent-Based Simulation 4 2003, April 28-20, Montpellier, France. "Statistical Validation of Spatial Patterns in Agent-Based Models"
http://www.cscs.umich.edu/sluce/publications/sluce-abs.pdf
Cellular Automata
Note: For those unfamiliar with cellular automata, the most famous example is the so-called "Game of Life". Here's an applet version of a NetLogo model of the Game of Life, http://ccl.northwestern.edu/netlogo/models/LifeTurtle-Based . (Read the instructions on that page, then click the "Run Life Turtle-Based in your browser" link at the top.) The Game of Life is an example of two dimensional cellular automata. For an example of the workings of one dimensional cellular automata (discussed in the Hordijk paper), see http://ccl.northwestern.edu/netlogo/models/CA1DRule90 .
Self-Organization
"Quantifying Self-Organization with Optimal Predictors." Cosma Shalizi, Kristina Shalizi, and Robert Haslinger. Physical Review Letters, v93, 118701 (2004). http://link.aps.org/doi/10.1103/PhysRevLett.93.118701
- Cyclic CA model here: http://cs.northwestern.edu/~fjs750/models/cyclic-ca.html
"Self Organization and Coordination", Scott Page, Computational Economics, v18, p25-48, 2001. http://www.springerlink.com/content/v5427h2261g73hj4/
Evolution of Cooperation
V. A. A. Jansen and M. van Baalen. "Altrusim through beard chromodynamics". Nature. Vol 440| 30 March 2006. http://dx.doi.org/10.1038/nature04387
Science Issue with three interesting articles:, Science, Volume 314, Issue 5805, dated December 8 2006, is now available at, http://www.sciencemag.org/content/vol314/issue5805/index.dtl?etoc
- Group Competition, Reproductive Leveling, and the Evolution of Human Altruism, Samuel Bowles, p. 1569 http://www.sciencemag.org/cgi/content/abstract/314/5805/1569?etoc
- EVOLUTION: The Puzzle of Human Sociality, Robert Boyd, p. 1555 http://www.sciencemag.org/cgi/content/summary/314/5805/1555?etoc
- Five Rules for the Evolution of Cooperation, Martin A. Nowak, p. 1560, http://www.sciencemag.org/cgi/content/abstract/314/5805/1560?etoc
Evolution of indirect reciprocity. Nature, 2005.
http://www.ped.fas.harvard.edu/people/faculty/publications_nowak/nature05c.pdf
Networks and Games
"A simple rule for the evolution of cooperation on graphs and social networks", Hisashi Ohtsuki, Christoph Hauert, Erez Lieberman, Martin A. Nowak, 2006 (3 pages), http://www.nature.com/nature/journal/v441/n7092/abs/nature04605.html
"The Role of Social Structure in the Maintenance of Cooperative Regimes", Michael Cohen, Rick Riolo, Robert Axelrod, 2001. Rationality and Society, 13.1. http://fordschool.umich.edu/research/pdf/Role_of_Social_Structure.pdf
"Social dimemas in an online social network: the structure and evolution of cooperation", Feng Fu, Xiaojie Chen, Lianghuan Liu, and Long Wang, 2007, http://www.arxiv.org/PS_cache/physics/pdf/0701/0701323.pdf
1 The Economics of Social Networks
(http://www.stanford.edu/~jacksonm/netect.pdf)
The science of social networks is a central ?eld of sociological study,
a major application
of random graph theory, and an emerging area of study by economists,
statistical physicists
and computer scientists. While these literatures are (slowly) becoming
aware of each other,
and on occasion drawing from one another, they are still largely
distinct in their methods,
interests, and goals. Here, my aim is to provide some perspective on the
research from these
literatures, with a focus on the formal modeling of social networks and
the two major types
of models: those based on random graphs and those based on game
theoretic reasoning.
I highlight some of the strengths, weaknesses, and potential synergies
between these two
network modeling approaches.
2. Network Games (http://www.stanford.edu/~jacksonm/networkgames.pdf)
In a variety of contexts { ranging from public goods provision to
information collec-
tion { a person's well being depends on her own action as well as on the
actions taken
by her neighbors. We develop a framework to analyze such strategic
interactions when
neighborhood structure, modeled in terms of an underlying network of
connections,
a®ects payo®s. Our framework has two distinctive features: it permits a
variety of
payo® functions and applications, and it allows for variations in terms
of how much
players know about the overall network structure. We provide a number of
results
characterizing how the network structure, an individual's position
within the network,
the nature of games (strategic substitutes versus complements and
positive versus neg-
ative externalities), and the level of information (incomplete versus
complete), shape
individual behavior and payo®s.
3. The Formation of Networks with Transfers among Players
(http://www.stanford.edu/~jacksonm/nettransfer.pdf)
We examine the formation of networks among a set of players whose payo¤s
depend
on the structure of the network. We focus on games where players may
bargain by
promising or demanding transfer payments when forming links, and vary
three aspects
of the game: (i) whether players can only make transfers to (and receive
transfers from)
players to whom they are directly linked, or whether they can also
subsidize links that
they are not directly involved in, (ii) whether or not transfers
relating to a given link
can be made contingent on the full resulting network or only on the link
itself, and
(iii) whether or not players can pay other players to refrain from
forming links. We
characterize the networks that are supported under these variations and
show how each
of the above aspects either accounts for a speci?c type of externality,
or deals with the
combinatorial nature of network payo¤s.
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