A view of evolution is presented in this paper (a two paper series), intended as a methodological infrastructure for modeling spatio-cultural systems (the design outline of such a model is presented in paper II). A motivation for the re-articulation of evolution as information dynamics is the phenomenologically discovered prerequisite of embedding a meaning-attributing apparatus in any and all models of spatio-cultural systems. An evolution is construed as the dynamics of a complex system comprised of memory devices, connected in an ordered (...) fashion (not randomly) by information-exchanges. An information-exchange transpires when the recipient system adopts a strategy (a continuum of events) that eventually changes its structure; namely, after the exchange, it contains and conveys different information. These memory devices—sub-systems—are also similarly constructed complex system. Only a part of the information is retained by a system in its physical-memory storage, which eventually loses this function too, when the ability to retrieve a common enough structure is lost. The entire amount of information is a system’s structure of connections (information exchanges); it is contained (apparently stored) dynamically when a system is observed in a temporarily stable state. This temporary permanence—robustness and resilience—is attained dynamically; namely, enabled by changes taking place in its sub-systems and in each of their sub-systems. Therefore, for modeling such a system a multi-layer/multi-scale approach is preferable. It enables the addition and subtraction of an interim scale and the consideration of such a scale as a micro or a macro (thus initiating a maneuver up or down scale) according to an ad-hoc requirement of the model, which imitates an envisaged sub system (called an ‘Inner World’), to which a certain range of decisions is relegated. This dynamics is driven (in time) by dynamically originated information growth, as defined by Shannon; i.e. by the fact that each of certain state transitions have occurred sometime in the past of the system just so and not otherwise, and by the fact that they have occurred in a certain order. Therefore, each ‘history’ and memory retrieval availability of information is unique, and thus can be used to differentiate meanings. Hence, there cannot be a comprehensive solution to the meaning attribution model-design challenge. However, the observation that at the core of each envisaged complex system, moving in time according to a rounded logic, there is an information manipulating device, operating necessarily according to a Boolean logic, can be copied into the design of a model. This observation enables, therefore, the embedding of a specific, locally fitted, meaning attributing device, which is an information manipulating mechanism (it splices/attaches one segment of information to another—its meaning). However, this is just a framework; the actual solution has still to be found locally—for each subject system. Such a solution is demonstrated for the change in location or layout in the Israeli city in paper II. (shrink)

A model of a spatio-cultural sub-context (enfolded in a wider scope context) is presented in the form of a blue print of a Complex System with a two-stage decision engine at its core. The engine first attaches a meaning to analyzable datum, and then decides whether to keep or change it. It does not alter already stored meanings but is designed to search for data to be converted into additional stored meanings and improve the accuracy of correspondence of their spatial (...) and cultural range of relevance. Meaning is reduced to the choice of a strategy—a future continuum of events; a choice dependent on a unique Evolutionary Path, a past continuum of events specific enough to lead to the current temporarily stable state of a spatio-cultural category. It is a blue print for a program that can emulate decisions to initiate changes in the environment in which a collective of culture partners resides; changes consisting of movements from one location to another or in the layout of its current location. The model is proposed at a low cultural resolution and is applicable, after suitable modifications, to a majority of city/period pairs. However, any such model has to be city/period specific. It is illustrated with a design for analyzing changes in the Israeli city, in particular in Tel Aviv. (shrink)

This is the last in a series of three papers on the history of the Lenz–Ising model from 1920 to the early 1970s. In the first paper, I studied the invention of the model in the 1920s, while in the second paper, I documented a quite sudden change in the perception of the model in the early 1960s when it was realized that the Lenz–Ising model is actually relevant for the understanding of phase transitions. In this article, which is self-contained, (...) I study how this realization affected attempts to understand critical phenomena, which can be understood as limiting cases of (first-order) phase transitions, in the epoch from circa 1965 to 1970, where these phenomena were recognized as a research field in its own right. I focus on two questions: What kinds of insight into critical phenomena was the employment of the Lenz–Ising model thought to give? And how could a crude model, which the Lenz–Ising model was thought to be, provide this understanding? I document that the model played several roles: At first, it played a role analogous to experimental data: hypotheses about real systems, in particular relations between critical exponents and what is now called the hypothesis of scaling, which was advanced by Benjamin Widom and others, were confronted with numerical results for the model, in particular the model’s so-called critical exponents. A positive result of a confrontation was seen as positive evidence for this hypothesis. The model was also used to gain insight into specific aspects of critical phenomena, for example that diverse physical systems exhibit similar behavior close to a critical point. Later, a more systematic program of understanding critical phenomena emerged that involved an explicit formulation of what it means to understand critical phenomena, namely, the elucidation of what features of the Hamiltonian of models lead to what kinds of behavior close to critical points. Attempts to accomplish this program culminated with the so-called hypothesis of universality, put forward independently by Robert B. Griffiths and Leo P. Kadanoff in 1970. They divided critical phenomena into classes with similar critical behavior. I also study the crucial role of the Lenz–Ising model in the development and justification of these ideas. (shrink)

Complexity sciences have become famous worldwide thanks to several popular books that served as echo chambers of their promises. These consisted in departing from “classical science” defined as deterministic, reductionist, analytic and mono-disciplinary. Their founders and supporters declared that complexity sciences were going to give rise (or that they have given rise) to a post-Laplacian, antireductionist, holistic and interdisciplinary approach. By taking a closer look at their content and practices, I argue in this article that, because of their physics-oriented, computationalist, (...) and mathematical assumptions, complexity sciences have paradoxically produced knowledge at odds with these four tenets. (shrink)

Since their inception in the 1980s, complexity sciences have been described as a revolutionary new domain of research. By describing some of the practices and assumptions of its representatives, the present article shows that this field is an association of subdisciplines laying on existing disciplinary footholds. The general question guiding us here is: On what basis do complexity scientists consider their inquiry methods and results as valuable? To answer it, I describe five “epistemic argumentative regimes,” namely the ways in which (...) complexity scientists argue the credibility of their research, and five “ontological views,” that is the ways in which they interpret the material and formal causes of their study objects and models. Finally, the article proposes the term of “regime of evidence” to designate the specific combination of one ontological view with one or more epistemic argumentative regimes. (shrink)

Complexity sciences are one of the most mediatized scientific fields of the last 40 years. While this domain has attracted the attention of many philosophers of science, its normative views have not yet been the object of any systematic study. This article is a contribution to the thin social science literature about complexity sciences and proposes a contribution focused on an analysis of the origins, models, and organization of the Santa Fe Institute (SFI), cradle of the field. The paper defends (...) the thesis that the notion of “complex adaptive systems” bears a project of naturalization of society through numerical and evolutionary lenses by promoting a Darwinian and capitalist view of the economy. At the same time, such a view has been embodied in the very way of functioning of the institute, which was conceived as an agile organization in a competitive environment and which relies on a fundraising philosophy that tends to commodify science. From a theoretical viewpoint, this text is anchored in the field of Science and Technology Studies and particularly in the coproductionist paradigm, which theorizes the dynamic entanglement of science and society. In terms of empirical sources, the article is based on interviews conducted by the author, and on the SFI's scientific publications as well as institutional archives. (shrink)

The goal of the present article is to contribute to the epistemology and methodology of computer simulations. The central thesis is that the process of simulation modeling takes the form of an explorative cooperation between experimenting and modeling. This characteristic mode of modeling turns simulations into autonomous mediators in a specific way; namely, it makes it possible for the phenomena and the data to exert a direct influence on the model. The argumentation will be illustrated by a case study of (...) the general circulation models of meteorology, the major simulation models in climate research. (shrink)

This paper explores the case of using robots to simulate evolution, in particular the case of Hamilton’s Law. The uses of robots raises several questions that this paper seeks to address. The first concerns the role of the robots in biological research: do they simulate something or do they participate in something? The second question concerns the physicality of the robots: what difference does embodiment make to the role of the robot in these experiments. Thirdly, how do life, embodiment and (...) social behavior relate in contemporary biology and why is it possible for robots to illuminate this relation? These questions are provoked by a strange similarity that has not been noted before: between the problem of simulation in philosophy of science, and Deleuze’s reading of Plato on the relationship of ideas, copies and simulacra. (shrink)

Reasons are given to justify the claim that computer simulations and computational science constitute a distinctively new set of scientific methods and that these methods introduce new issues in the philosophy of science. These issues are both epistemological and methodological in kind.

The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...) primary and secondary qualities from Galileo onward. It is arguably one of several conceptions involved in Whewell’s method of the “consilience of inductions” (Laudan 1971) and is to be found in several places in Peirce. (From M. Brewer and B. Collins, eds., (1981); Scientific Inquiry in the Social Sciences (a festschrift for Donald T. Campbell), San Francisco: Jossey-Bass, pp. 123–162.). (shrink)