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| <head><title>Santa Fe Institute Workshop Summary Description//</title>
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| <div class="maketitle">
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| <h2 class="titleHead"><a
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| id="x1-1doc"></a>
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| Santa Fe Institute Workshop<br />
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| Summary Description
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| </h2>
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| <div class="RRAP">
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| <span
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| class="cmr-10">(</span><span class="date" ><span
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| class="cmr-10">Dated: December 13, 2010</span></span><span
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| class="cmr-10">)</span>
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| </div>
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| <div class="abstractheading"></div>
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| <div class="abstract">
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| <!--l. 50--><p class="noindent" ><span
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| class="cmbx-12">Title</span><span
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| class="cmr-12">:</span><br
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| class="newline" /><span
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| class="cmr-12">  Randomness, Structure, and Causality:</span><br
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| class="newline" /><span
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| class="cmr-12"> </span><span
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| class="cmr-12"> </span><span
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| class="cmr-12">  Measures of complexity from theory to applications</span><br
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| class="newline" />
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| <span
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| class="cmbx-12">Dates</span><span
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| class="cmr-12">: 9-13 January 2011</span><br
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| class="newline" /> <span
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| class="cmbx-12">Location</span><span
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| class="cmr-12">: Santa Fe Institute, Santa Fe, New Mexico</span><br
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| class="newline" /> <span
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| class="cmbx-12">Organizers</span><span
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| class="cmr-12">:</span><br
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| class="newline" /><span
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| class="cmr-12">  Jim Crutchfield (SFI and UC Davis, chaos@ucdavis.edu)</span><br
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| class="newline" /><span
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| class="cmr-12">  Jon Machta (SFI and University of Massachusetts, machta@physics.umass.edu)</span>
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| </div>
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| <div class="frontpagefootnotes">
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| </div>
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| </div>
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| <a
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| id="likesection.1"></a>
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| <h3 class="likesectionHead"><a
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| id="x1-1000"></a>Description</h3>
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| <!--l. 75--><p class="noindent" >In 1989, SFI hosted a workshop—<span
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| class="cmti-10x-x-109">Complexity, Entropy, and the Physics of Information</span>—on fundamental
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|
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|
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| definitions of complexity. This workshop and the proceedings that resulted [<a
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| href="#XZure89a">1</a>] stimulated a great deal of
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| thinking about how to define complexity. In many ways—some direct, many indirect—the foundational
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| theme colored much of SFI’s research planning and, more generally, the evolution of complex system
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| science since then. Complex systems science has considerably matured as a field in the intervening
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| decades and we believe it is now time to revisit fundamental aspects of the field in a workshop format at
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| SFI. Partly, this is to take stock; but it is also to ask what innovations are needed for the coming
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| decades, as complex systems continues to extend its influence in the sciences, engineering, and
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| humanities.
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| <!--l. 90--><p class="indent" > The goal of the workshop is to bring together workers from a variety of fields to discuss structural and
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| dynamical measures of complexity appropriate for their field and the commonality between these
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| measures. Some of the questions that we will address in the workshop are:
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| <ol class="enumerate1" >
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| <li
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| class="enumerate" id="x1-1002x1">Are there fundamental measures of complexity that can be applied across disciplines or are
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| measures of complexity necessarily tied to particular domains?
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| </li>
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| <li
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| class="enumerate" id="x1-1004x2">How is a system’s causal organization, reflected in models of its dynamics, related to its
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| complexity?
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| </li>
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| <li
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| class="enumerate" id="x1-1006x3">Are there universal mechanisms at work that lead to increases in complexity or does
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| complexity arise for qualitatively different reasons in different settings?
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| </li>
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| <li
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| class="enumerate" id="x1-1008x4">Can we reach agreement on general properties that all measures of complexity must have?
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| </li>
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| <li
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| class="enumerate" id="x1-1010x5">How would the scientific community benefit from a consensus on the properties that measures
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| of complexity should possess?</li></ol>
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| <!--l. 112--><p class="indent" > It’s a four-day workshop with about 20 or so participants. We will have a stimulating and highly
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| interdisciplinary group with representation from physics, biology, computer science, social science, and
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| mathematics. An important goal is to understand the successes and difficulties in deploying complexity
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| measures in practice. And so, participants come from both theory and experiment, with a particular
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| emphasis on those who can constructively bridge the two.
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| <!--l. 120--><p class="indent" > Since the 1989 SFI workshop, a number of distinct strands have developed in the effort to measure
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| complexity. Several of the well-developed strands are based on
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|
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|
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| <ul class="itemize1">
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| <li class="itemize">Predictive information and excess entropy [<a
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| href="#XJunc79">2</a>–<a
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| href="#XCrut01a">7</a>],
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| </li>
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| <li class="itemize">Statistical complexity and causal structure [<a
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| href="#XCrut88a">8</a>–<a
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| href="#XShal98a">10</a>],
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| </li>
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| <li class="itemize">Logical depth and computational complexity [<a
| |
| href="#XBenn90">11</a>–<a
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| href="#XMach06a">15</a>], and
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| </li>
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| <li class="itemize">Effective complexity [<a
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| href="#XGeLl96">16</a>, <a
| |
| href="#Xay-2008">17</a>].</li></ul>
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| <!--l. 134--><p class="noindent" >While these measures are broadly based on information theory or the theory of computation, the full set of
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| connections and contrasts between them is not well developed. Some have sought to clarify
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| the relationship among these measures [<a
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| href="#XCrut01a">7</a>, <a
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| href="#Xay-2008">17</a>–<a
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| href="#XFeld98b">20</a>] and so another goal of the workshop is
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| to foster this kind of comparative work by bringing together researchers developing various
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| measures.
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| <!--l. 141--><p class="indent" > A second motivation for the workshop is to bring together workers interested in foundational
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| questions—who are mainly from the physics, mathematics, and computer science communities—with
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| complex systems scientists in experimental, data-driven fields who have developed quantitative
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| measures of complexity, organization, and emergence that are useful in their fields. The range of
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| data-driven fields using complexity measures is impressively broad: ranging from molecular
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| excitation dynamics [<a
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| href="#XNeru08a">21</a>] and spectroscopic observations of the conformational dynamics of
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| single molecules [<a
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| href="#XLi08a">22</a>] through modeling subgrid structure in turbulent fluid flows [<a
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| href="#XPalm00a">23</a>] and new
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| visualization methods for emergent flow patterns [<a
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| href="#XJani07a">24</a>] to monitoring market efficiency [<a
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| href="#XYang08a">25</a>] and the
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| organization of animal social structure [<a
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| href="#XAy07a">26</a>]. The intention is to find relations between the practically
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| motivated measures and the more general and fundamentally motivated measures. Can the
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| practically motivated measures be improved by an appreciation of fundamental principles? Can
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| fundamental definitions be sharpened by consideration of how they interact with real-world
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| data?
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| <!--l. 159--><p class="indent" > Overall, the workshop’s intention is to re-ignite the efforts that began with <span
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| class="cmti-10x-x-109">Complexity, Entropy,</span>
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| <span
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| class="cmti-10x-x-109">and the Physics of Information </span>workshop. A new level of rigor, in concepts and in analysis,
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| is now apparent in how statistical mechanics, nonlinear dynamics, information theory, and
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| computation theory can be applied to complex systems. The meteoric rise of both computer
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| power and machine learning has led to new algorithms that address many of the original
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| computational difficulties in managing data from complex systems and in estimating various
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| complexity measures. Given progress on all these fronts, the time is ripe to develop a much closer
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|
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|
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| connection between fundamental theory and applications in many areas of complex systems
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| science.
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| <!--l. 1--><p class="indent" >
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| <a
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| id="likesection.2"></a><a
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| id="Q1-1-1"></a>
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| <!--l. 1--><p class="noindent" >
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