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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> <html> <head> <link href="https://bactra.org/plain-style.css" rel="stylesheet" type="text/css"> <title>Complexity (and/or "Complex Systems")</title>        </head> <body>   <P> <P></P><!-- Access to MathJax through the version I'm hosting on bactra.org !--><!-- but only IF mathmode is activated via meta_mathmode !-->  <script> window.MathJax = {  tex: {    inlineMath: [['$','$'], ['\\(','\\)']],    processEscapes: true,    autoload: {      color: [],      colorv2: ['color']    },    packages: {'[+]': ['noerrors']}  },  options: {    ignoreHtmlClass: 'tex2jax_ignore',    processHtmlClass: 'tex2jax_process'  },  loader: {    load: ['[tex]/noerrors']  }};</script>      <cite><a href="http://bactra.org/notebooks">Notebooks</a></cite> <div class="text"><div class="left"><h2>Complexity (and/or "Complex Systems")</h2> <i><a href="faq.html#5.4">Last update</a>: 21 Apr 2025 21:17</i><br><i><a href="faq.html#5.4">First version</a>: 25 September 1997 (or earlier?); major revisions 23 November 2002, and (even more substantial) 18 October 2024.</i> <hr> <P>   <P>If pressed to explain what I mean by this, I'd say that it's processesshowing some combination of non-linearity and lots of strongly interactingcomponents --- but ones where the interactions aren't <em>so</em> strong thatthere is an effective low-dimensional description.  The common thread isthat you need lots of <a href="information-theory.html">information</a> tounderstand what's going on.  As for more precise definitions, well,I give <a href="complexity-measures.html">complexity measures</a> their ownnotebook for a reason.  My fuller views are expounded in some of my papers,linked to below. <P>My own views on this subject are, naturally, hard to separate from the factthat I've been going to the <a href="http://www.santafe.edu/">Santa FeInstitute</a> since 1997, worked there full time 1998--2002, have been on itsexternal faculty since the '00s, etc.  That place, and the scientific networkaround it, has not only provided me with training, resources and professionalopportunities, but mentors, collaborators, close personal friends, aprofessional agenda, and sense of belonging to something valuable.  Like anyhome, it has moments when the other occupants make me roll my eyes, but itwould be absurd for me to pretend to be an impartial critic.  I'm only tooaware that someone else interested in the same topics, but not inducted intothe same <a href="http://bactra.org/weblog/368.html">epistemic community</a>,the same network-and-tradition, might well make very different judgments aboutthe literature... <P><em>To develop, someday</em>: An exposition of how the whole field is a"series of footnotes" to <a href="wiener.html">Norbert Wiener</a> and <a href="simon.html">Herbert Simon</a>. <P>The linkage/references here are sparser than they could be, because today my lumper/splitter pendulum has swung towards "split", and I've moved a lot ofstuff to the more specialized notebooks.  <ul>See also:	<li><a href="adaptation.html">Adaptation</a>	<li><a href="agent-based-modeling.html">Agent-based Modeling</a>	<li><a href="ai.html">Artificial Intelligence</a>	<li><a href="alife.html">Artificial Life</a>	<li><a href="ashby.html">W. Ross Ashby</a>	<li><a href="biological-order.html">Biological Order and Levels ofOrganization</a>	<li><a href="cellular-automata.html">Cellular Automata</a>	<li><a href="chaos.html">Chaos and Non-linear Dynamics</a>	<li><a href="cognitive-science.html">Cognitive Science</a>	<li><a href="collective-cognition.html">Collective Cognition</a>	<li><a href="complexity-measures.html">Complexity Measures</a>	<li><a href="complex-networks.html">Complex Networks</a>	<li><a href="computation.html">Computation, Automata, Languages</a>	<li><a href="cybernetics.html">Cybernetics</a>	<li><a href="darwin-machines.html">Darwin Machines</a>	<li><a href="development-bio.html">Developmental Biology</a>	<li><a href="dissipative-structures.html">Dissipative Structures</a>	<li><a href="ecology.html">Ecology</a>	<li><a href="economics.html">Economics</a>	<li><a href="edge-of-chaos.html">Edge of Chaos</a>	<li><a href="emergent-properties.html">Emergent Properties</a>	<li><a href="ergodic-theory.html">Ergodic Theory</a>	<li><a href="evolving-local-rules.html">Evolving Local Rules to Perform Global Computations</a>	<li><a href="evolution.html">Evolution</a>	<li><a href="evolution-of-complexity.html">Evolution of Complexity</a>	<li><a href="evol-comp.html">Evolutionary Computation</a>	<li><a href="evol-econ.html">Evolutionary Economics</a>	<li><a href="evol-game-theory.html">Evolutionary Game Theory</a>	<li><a href="non-stationary-forecasting.html">Forecasting Non-Stationary Processes, and Estimating Their Parameters</a>	<li><a href="flocking-and-swarms.html">Flocking and Swarms</a>	<li><a href="homophily-vs-influence.html">Homophily and Influence in Social Networks</a>	<li><a href="information-flow.html">Information Flow</a>	<li><a href="information-theory.html">Information Theory</a>	<li><a href="interacting-particle-systems.html">Interacting Particle Systems</a>	<li><a href="institutions.html">Institutions and Organizations</a>	<li><a href="koopman-operator-modeling.html">Koopman Operators for Modeling Dynamical Systems and Time Series</a>	<li><a href="large-deviations.html">Large Deviations</a>	<li><a href="learning-games.html">Learning in Games</a>	<li><a href="learning-theory.html">Learning Theory (Formal, Computational or Statistical)</a>	<li><a href="learning-inference-induction.html">Machine Learning, Statistical inference and Induction</a>	<li><a href="max-ent.html">Maximum Entropy Methods (MaxEnt)</a>	<li><a href="micro-macro.html">Macroscopic Consequences of MicroscopicInteractions</a>	<li><a href="social-science-methodology.html">Methodology for the Social Sciences</a>	<li><a href="multi-agent-systems.html">Multi-Agent Systems</a>	<li><a href="neural-nets.html">Neural Nets, Connectionism, Perceptrons;</a>	<li><a href="neuroscience.html">Neuroscience</a>	<li><a href="noneq-sm.html">Nonequilibrium Statistical Mechanics andThermodynamics</a>	<li><a href="parallel.html">Parallel and Distributed Computing</a>	<li><a href="pattern-formation.html">Pattern Formation</a>	<li><a href="phase-transitions.html">Phase Transitions and Critical Phenomena</a>	<li><a href="physics-computation-information.html">Physics of Computationand Information</a>	<li><a href="physical-biology.html">Physical Principles in Biology</a>	<li><a href="physics.html">Physics</a>	<li><a href="power-laws.html">Power Law Distributions and Long-RangeCorrelations</a>	<li><a href="prediction-process.,html">Prediction Processes; Markovian (and Conceivably Causal) Representations of Stochastic Processes</a>	<li><a href="prigogine.html">Ilya Prigogine</a>	<li><a href="qwerty.html">QWERTY</a>	<li><a href="nk-networks.html">Random Boolean Networks, Nk Networks</a>	<li><a href="schelling-model.html">Schelling model</a>	<li><a href="self-organization.html">Self-organization</a>	<li><a href="signal-transduction.html">Signal Transduction, Control of Metabolism, and Gene Regulation</a>	<li><a href="simon.html">Herbert Simon</a>	<li><a href="simulations.html">Simulations</a>	<li><a href="social-contagion.html">Social Contagion</a>	<li><a href="sociology.html">Sociology</a>	<li><a href="spin-glasses.html">Spin Glasses</a>	<li><a href="stability-and-complexity-of-ecosystems.html">Stability and Complexity of Ecosystems</a>	<li><a href="state-space-reconstruction.html">State-Space Reconstruction</a>	<li><a href="dependent-learning.html">Statistical Learning Theory with Dependent Data</a>	<li><a href="stat-mech.html">Statistical Mechanics</a>	<li><a href="symbolic-dynamics.html">Symbolic Dynamics</a>	<li><a href="tsallis.html">Tsallis Statistics</a>	<li><a href="computation-by-physical-systems.html">When Do Physical Systems Compute?</a>	<li><a href="wiener.html">Norbert Wiener</a>	</ul> <ul>Recommended, big picture, less technical:	<li>Robert Axelrod and Michael D. Cohen, <cite>Harnessing Complexity:Organizational Implications of a Scientific Frontier</cite>	<li>Jack Cohen and Ian Stewart, <cite>The Collapse of Chaos</cite> [Agreat book, except that, as they themselves say of Dawkins, the philosophy iscompletely backwards, especially on <ahref="reductionism.html">reductionism</a> and <ahref="emergent-properties.html">emergent properties</a>.]	<li><a href="john-holland.html">John Holland</a>, <cite><ahref="http://bactra.org/reviews/holland-on-emergence/">Emergence</a></cite>	<li>Steven Johnson, <cite>Emergence: The Connected Lives of Ants,Brains, Cities and Software</cite> [What I buy my relatives when they askme what all the fuss is about.]	<li>David C. Krakauer (ed.), <cite><a href="https://www.sfipress.org/books/worlds-hidden-in-plain-sight">Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984--2019</a></cite>	<li>Melanie Mitchell, <cite>Complexity: A Guided Tour</cite> [Disclaimer: I used to work for Melanie.]	<li>Heinz Pagels, <cite>The Dreams of Reason: The Computer and the Riseof the Sciences of Complexity</cite> [What I <em>used</em> to buy my relatives.Deserves to be brought back into print.]	<li><a href="simon.html">Herbert Simon</a>, <cite>The Sciences of theArtificial</cite> [Especially the last chapter, "The Architecture ofComplexity".]	</ul> <ul>Recommended, big picture, textbooks (or close enough):	<li>Remo Badii and Antonio Politi, <cite><ahref="http://bactra.org/reviews/badii-and-politi/">Complexity: HierarchicalStructures and Scaling in Physics</a></cite>	<li>Nino Boccara, <cite><ahref="http://bactra.org/reviews/boccara/">Modeling Complex Systems</a></cite>	<li>Gary William Flake, <cite><a href="http://bactra.org/reviews/computational-beauty-of-nature/">The Computational Beauty of Nature</a></cite>	<li>Josef Honerkamp, <cite>Stochastic Dynamical Systems: Concepts,Numerical Methods, Data Analysis</cite>	<li>{1988--1993} <cite>Lectures in Complex Systems</cite> [Proceedingsof the SFI summer schools]	<li>John H. Miller and ScottE. Page, <cite><a href="https://doi.org/10.1515/9781400835522">Complex AdaptiveSystems: An Introduction to Computational Models of Social Life</a></cite>[<a href="agent-based-modeling.html#cas">Brief comments/disclaimer</a>]	<li>Mitchel Resnick, <cite><a href="http://bactra.org/reviews/turtles-termites-traffic-jams/">Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds</a></cite>	</ul> <ul>Recommended, big picture, technical but not textbooks:	<li>Terry Bossomaier and David Green (eds.), <cite>ComplexSystems</cite>	<li>David C. Krakauer (ed.), <cite><a href="https://www.sfipress.org/books/foundational-papers-in-complexity-science">Foundational Papers in Complexity Science, 1922--2000</a></cite> [Disclaimer 1: I'm a contributor, having provided an introduction and annotations to a paper in volume 1 (<a href="rosenblueth.html">More on this.</a>).  Disclaimer 2: I haven't seen volume 4 yet.]	<li>M. E. J. Newman, "Complex Systems: A Survey", <cite>AmericanJournal of Physics</cite> <strong>79</strong> (2011): 800--810,<a href="http://arxiv.org/abs/1112.1440">arxiv:1112.1440</a> [literaturesurvey]	<li>Michael Strevens, "How Are the Sciences of Complex Systems Possible?", <a href="http://dx.doi.org/10.1086/505471"><cite>Philosophy of Science</cite><strong>72</strong> (2005): 531--556</a>	</ul> <ul>Recommended, close-ups, more technical:	<li>John Bickle, "Understanding Neural Complexity: A Role forReduction", <cite>Minds and Machines</cite> <strong>11</strong> (2001):467--481	<li>John Tyler <a href="j-t-bonner.html">Bonner</a>, <cite><ahref="http://bactra.org/reviews/evolution-of-complexity/">TheEvolution of Complexity, by Means of Natural Selection</a></cite>	<li>The work of the <ahref="computational-mechanics.html">computational mechanics group</a> at SantaFe is, IMHO, the closest anyone has got yet to a general, rigorous way oftackling complexity, and it is scandalously little-known.  [That sentence wasthere years before I became part of the group --- and is still there yearsafter I left.]	<li>George Cowan, David Pines and D. Melzner (eds.), <cite>Complexity: Metaphors, Models, and Reality</cite>	<li>Joshua M. Epstein and Robert Axtell, <cite><a href="https://doi.org/10.7551/mitpress/3374.001.0001">Growing Artificial Societies: Social Science from the Bottom Up</a></cite>	<li>J. Doyne Farmer, Alan Lapedes, Norman Packard and Burton Wendroff(eds.), <cite>Evolution, Games, and Learning: Models for Adaptation in Machinesand Nature</cite> (a.k.a. <a href="https://doi.org/10.1016/0167-2789(86)90227-7"><cite>Physica D</cite> <strong>22</strong> (1986)</a>.)	<li>Stephanie Forrest (ed.), <cite>Emergent Computation:Self-Organizing, Collective, and Cooperative Phenomena in Natural andArtificial Computing Networks</cite> (a.k.a. <a href="https://doi.org/10.1016/0167-2789(90)90063-U"><cite>Physica D</cite><strong>42</strong> (1990)</a>)	<li>StuartKauffman, <cite><a href="https://doi.org/10.1093/oso/9780195079517.001.0001"name="ooo">The Origins of Order: Self-Organization and Selection inEvolution</a></cite> [Highly interesting and valuable, but to be read with somecaution.  The writing is often confused, and, frankly, in subsequent decades,many of the ideas (e.g., "<a href="edge-of-chaos.html">the edge of chaos</a>")did not pan out.  Still extremely important, not least for its fertility ofinvention.]	<li>D. L. Stein, "Spin Glasses: Still Complex After All TheseYears?" <ahref="http://arxiv.org/abs/cond-mat/0301104">cond-mat/0301104</a>	<li>Daniel L. Stein and Charles M. Newman, <cite><a href="https://doi.org/10.1515/9781400845637">Spin Glasses and Complexity</a></cite>	</ul> <ul>Modesty forbids me to recommend:	<li>CRS, "Methods and Techniques of Complex Systems Science: AnOverview", chapter 1 (pp. 33--114) in Deisboeck and Kresh (eds.), <cite>ComplexSystems Science inBiomedicine</cite>, <a href="http://arxiv.org/abs/nlin.AO/0307015">nlin.AO/0307015</a>	<li>CRS, <a href="https://www.stat.cmu.edu/~cshalizi/462/">Chaos,Complexity, and Inference</a> [Materials for an undergraduatestatistics class I taught in 2008 and 2009]	<li>My papers listed under <a href="complexity-measures.html">complexity measures</a>	</ul> <ul>Dis-recommended:	<li>I have a long list, available upon request.  I may add it heresometime when I'm feeling more full of venom than the present.	</ul> <ul>To read:	<li>Claes Andersson, "Inverse Ontomimetic Simulation: a window on complex systems", <a href="https://philsci-archive.pitt.edu/5304/">phil-sci/5304</a> (2009)	<li>Fatihcan Atay, Sarika Jalan and J&uuml;rgen Jost, "Randomness,chaos, andstructure", <a href="http://arxiv.org/abs/0711.4293">arxiv:0711.4293</a>	<li>Sunny Auyang, <cite>Foundations of Complex Systems Theories: InEconomics, Evolutionary Biology, and Statistical Physics</cite>	<li>William Bechtel and Robert C. Richardson, <cite>Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research</cite>	<li>Richard K. Belew and Melanie Mitchell (eds.), <cite>Adaptive Individuals in Evolving Populations: Models and Algorithms</cite>	<li><a href="http://www.biol.unt.edu/~burggren/publications.html">W. W.Burggren</a> and M. G. Monticino, "Assessing Physiological Complexity",<cite>Journal of Experimental Biology</cite> <strong>208</strong> (2005):3221--3232 [<a href="http://www.biol.unt.edu/~burggren/PDFs/2005/Burggren%20and%20Monticino%202005%20JEB.pdf">Reprint</a>]	<li>Eric J. Chaisson		<ul>		<li><cite>Cosmic Evolution : The Rise of Complexity inNature</cite> [<ahref="http://www.americanscientist.org/template/BookReviewTypeDetail/assetid/17823">Reviewby Dan McShea in <cite>American Scientist</cite></a>; proposes definingcomplexity operationally as power dissipated per unit mass, according toMcShea.  Why this should be complexity, I don't get....]		<li>"Complexity: An Energetics Agenda", <cite>Complexity</cite><strong>9</strong> (2004): 14--21 [<ahref="http://www.tufts.edu/as/wright_center/eric/reprints/complexity_energetics_agenda.pdf">PDFreprint</a> from <ahref="http://www.tufts.edu/as/wright_center/eric/ericpage.html">Chaisson'swebsite</a>]		</ul>	<li>David Colander and Roland Kupers, <cite><a href="https://doi.org/10.2307/j.ctt6wq04g">Complexity and the Art of Public Policy: Solving Society's Problems from the Bottom Up</a></cite> [See also the review by Kirman, link below]	<li>Gerald Gaus, <cite><a href="https://doi.org/10.1093/oso/9780190648978.001.0001">The Open Society and Its Complexities</a></cite>	<li>Nick Gessler, <ahref="http://www.sscnet.ucla.edu/anthro/gessler/">Artificial Culture:Experiments in Synthetic Anthropology</a>	<li>Sebastian Grauwin, Guillaume Beslon, Eric Fleury, Sara Franceschelli, C&eacute;line Robardet, Jean-Baptiste Rouquier, Pablo Jensen, "Complex Systems Science: Dreams of Universality, Reality of Interdisciplinarity", <a href="http://arxiv.org/abs/1206.2216">arxiv:1206.2216</a>	<li>Claudius Gros, <cite><a href="https://doi.org/10.1007/978-3-319-16265-2">Complex and Adaptive Dynamical Systems: A Primer</a></cite>, <a href="http://arxiv.org/abs/0807.4838">arxiv:0807.4838</a> [Arxiv version seems to only be updated to the 2nd edition, but the paywalled one is the 4th...]	<li>Casey Helgeson, Vivek Srikrishnan, Klaus Keller and Nancy Tuana, "Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions", <a href="https://doi.org/10.1086/711501"><cite>Philosophy of Science</cite> <strong>88</strong> (2021): 213--233</a>	<li>John H. Holland		<ul>		<li><cite>Signals and Boundaries: Building Blocks for Complex Adaptive Systems</cite>		<li><cite>Complexity: A Very Short Introduction</cite>		</ul>	<li>Cliff Hooker (ed.), <cite>Philosophy of Complex Systems</cite>	<li>Giorgio Israel, "The Science of Complexity: EpistemologicalProblems andPerspectives", <ahrf="http://dx.doi.org/10.1017/S0269889705000621"><cite>Science inContext</cite> <strong>18</strong> (2005): 479--509 [From the abstract: "Theaim of the present article is to analyze the epistemological status attributedin the science of complexity to several fundamental ideas, such as those ofscientific law, objectivity, and prediction. The aim is to show that the hopeof superseding reductionism by means of concepts such as that of 'emergence'is fallacious and that the science of complexity proposes forms of reductionismthat are even more restrictive than the classical ones, particularly when itclaims to unify in a single treatment problems that vary widely in nature suchas physical, biological, and social problems."  Thanks to Prof. Israel fora reprint.]	<li>Alan Kirman, "Complexity and Economic Policy: A Paradigm Shift or a Change in Perspective? A Review Essay on David Colander and Roland Kupers's <cite>Complexity and the Art of Public Policy</cite>", <a href="https://doi.org/10.1257/jel.54.2.534"><cite>Journal of Economic Literature</cite> <strong>54</strong> (2016): 534--572</a>	<li>Meinard Kuhlmann, "Mechanisms in Dynamically Complex Systems",<a href="http://philsci-archive.pitt.edu/8442/">phil-sci/8442</a>	<li>James Ladyman and Karoline Wiesner, <cite><a href="https://doi.org/10.12987/9780300256130">What Is a Complex System?</a></cite>	<li>J. Stephen Lansing		<ul>		<li>"Complex Adaptive Systems", <ahref="http://dx.doi.org/10.1146/annurev.anthro.32.061002.093440"><cite>AnnualReview of Anthropology</cite> <strong>32</strong> (2003): 183--204</a>		<li><citE><a href="http://pup.princeton.edu/titles/8186.html">Perfect Order: Recognizing Complexity in Bali</a></cite>		</ul>	<li>J. Stephen Lansing and Murray P. Cox, <cite><a href="https://doi.org/10.1515/9780691197531">Islands of Order: A Guide to Complexity Modeling for the Social Sciences</a></cite>	<li>Simon Levin		<ul>		<li>"Complex Adaptive Systems: Exploring the known, theunknown, and the unknowable", <cite>Bulletin of the American MathematicalSociety</cite> <strong>40</strong> (2002): 3--19 [<ahref="http://www.princeton.edu/~seasplan/lifesciences/Bulletin%20Am%20Math%20Soc.pdf">PDF</a>.Survey, emphasis on evolutionary ecology]		<li><cite>Fragile Dominion: Complexity and theCommons</cite>		</ul>	<li>Christian Lindgren, "Information Theory for Complex Systems"(Online lecture notes, dated Jan. 2003)	<li>John H. Miller, <cite>A Crude Look at the Whole: The Science of Complex Systems in Business, Life, and Society</cite>	<li>Sandra Mitchell		<ul>		<li><cite><a href="https://doi.org/10.7208/9780226532653">Unsimple Truths: Science, Complexity, and Policy</a></cite>		<li><cite><a href="https://doi.org/10.1017/CBO9780511802683">Biological Complexity and Integrative Pluralism</a></cite>		</ul>	<li>Harold Morowitz, <cite>The Emergence of Everything</cite>	<li>Harold Morowitz and Jerome L. Singer (eds.), <cite>The Mind, theBrain, and Complex Adaptive Systems</cite>	<li>Scott E. Page, <cite><a href="https://www.jstor.org/stable/j.ctt7pfdp">Diversity and Complexity</a></cite>	<li>Giorgio Parisi, "Complex Systems: a Physicist's Viewpoint," <ahref="http://arxiv.org/abs/cond-mat/0205297">cond-mat/0205297</a>	<li>Max Pettersson, <cite>Complexity and Evolution</cite> [mostly ofinterest to me because of the introduction by <a href="needham.html">JosephNeedham</a>]	<li>Charles Rathkopf, "Network representation and complex systems",<a href="https://doi.org/10.1007/s11229-015-0726-0"><cite>Synthese</cite> <strong>195</strong> (2018): 55--78</a> [Color me skeptical of at least the first of the two main theses set forth in the abstract...]	<li>J. Barkley Rosser, Jr., "On the Complexities of Complex EconomicDynamics", <cite>Journal of Economic Perspectives</cite> <strong>13(4)</strong> (1999): 169--192 [<ahref="http://www.jstor.org/stable/2647018">JSTOR</a>]	<li>L. S. Schulman and B. Gaveau, "Complex systems under stochasticdynamics", <a href="http://arxiv.org/abs/cond-mat/0312711">cond-mat/0312711</a>	<li>Luigi Sertorio, <cite>Thermodynamics of Complex Systems: An Introduction to Ecophysics</cite>	<li>Paolo Sibani and Henrik Jeldtoft Jensen, <cite>Stochastic Dynamics of Complex Systems: From Glasses to Evolution</cite>	<li>Didier Sornette, <cite>Critical Phenomena in Natural Sciences:Chaos, Fractals, Self-Organization and Disorder: Concepts and Tools</cite>	<li>Michael Strevens, <cite>Bigger than Chaos: Understanding Complexitythrough Probability</cite>	<li>Tainter, <cite>Collapse of Complex Societies</cite>	<li>Stefan Thurner, Peter Klimek, and Rudolf Hanel, <cite><a href="https://doi.org/10.1093/oso/9780198821939.001.0001">Introduction to the Theory of Complex Systems</a></cite>	<li>V. I. Varhavsky and D. A. Pospelov, <cite><a href="https://archive.org/details/puppetswithoutstrings">Puppets Without Strings: Reflections on the Evolution and Control of Some Man-Made Systems</a></cite>	<li>M. Norton Wise (ed.), <cite><a href="http://www.dukeupress.edu/cgibin/forwardsql/search.cgi?template0=nomatch.htm&template2=books/book_detail_page.htm&user_id=31291923324&Bmain.item_option=1&Bmain.item=9958">Growing Explanations: HistoricalPerspectives on Recent Science</a></cite>	<li>Stanislaw Ulam, <cite><ahref="http://ark.cdlib.org/ark:/13030/ft9g50091s/">Analogies between Analogies</a></cite>	<li>Wiesner and Ladyman, "What Is a Complex System?"[<a href="http://www.maths.bristol.ac.uk/~enxkw/Publications_files/what_is_complexity.pdf">PDF preprint</a>]	</ul>  <ul>To write, someday:	<li><cite><a href="genealogy-of-complexity.html">The Genealogy of Complexity</a></cite>	<li><cite>The Statistical Analysis of Complex Systems</cite>	</ul>  </p> </div></div> <hr> <div class="footer"><P><a href="http://bactra.org/notebooks/complexity.html">permanent link for thisnote</a> &nbsp; <a href="http://bactra.org/notebooks/complexity.rss">RSS feed for thisnote</a></P></div><div class="foot"> <center> <cite><a href="http://bactra.org/notebooks">Notebooks</a></cite>: &nbsp; <a href="http://www.blosxom.com/">Powered by Blosxom</a> </center> </div> </body></html>

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