The emphasis on models hasn’t completely eliminated laws from scientific discourse and philosophical discussion. Instead, I want to argue that much of physics lies beyond the strict domain of laws. I shall argue that in important cases the physics, or physical understanding, does not lie either in laws or in their properties, such as universality, consistency and symmetry. I shall argue that the domain of application commonly attributed to laws is too narrow. That is, laws can still play an important, (...) though peculiar, role outside their strict domain of validity. I shall argue also that, by way of a trade-off, while the actual domain of application of laws should be seen as much broader. At the same time, what I call ‘anomic’ representational elements reveal themselves as central to the descriptive and explanatory power of theories and model: boundary conditions, state descriptions, structures, constraints, limits and mechanisms. I conclude with a brief consideration of how my discussion has consequences for discussion of understanding, unification, approximation and dispositional properties. I focus on examples from physics, macroscopic and microscopic, phenomenological and fundametal: shock waves, propagation of cracks, symmetry breaking, and others. This law-eccentric kind of knowledge is central to both modeling the world and intervening in it. (shrink)

Mesoscale modeling is often considered merely as a practical strategy used when information on lower-scale details is lacking, or when there is a need to make models cognitively or computationally tractable. Without dismissing the importance of practical constraints for modeling choices, we argue that mesoscale models should not just be considered as abbreviations or placeholders for more “complete” models. Because many systems exhibit different behaviors at various spatial and temporal scales, bottom-up approaches are almost always doomed to fail. (...) Mesoscale models capture aspects of multi-scale systems that cannot be parameterized by simple averaging of lower-scale details. To understand the behavior of multi-scale systems, it is essential to identify mesoscale parameters that “code for” lower-scale details in a way that relate phenomena intermediate between microscopic and macroscopic features. We illustrate this point using examples of modeling of multi-scale systems in materials science and biology, where identification of material parameters such as stiffness or strain is a central step. The examples illustrate important aspects of a so-called “middle-out” modeling strategy. Rather than attempting to model the system bottom-up, one starts at intermediate scales where systems exhibit behaviors distinct from those at the atomic and continuum scales. One then seeks to upscale and downscale to gain a more complete understanding of the multi-scale system. The cases highlight how parameterization of lower-scale details not only enables tractable modeling but is also central to understanding functional and organizational features of multi-scale systems. (shrink)

Computer aided modeling and simulation of nanomaterials can describe the correlation between the material’s microstructure and its macroscopic properties quantitatively. In this paper, we propose an integrated modeling, simulation, and visualization approach for designing nanomaterials. Firstly, a fast parametric modeling method for important nanomaterials such as graphene, nanotubes, and MOFs is proposed; secondly, the material model could be edited adaptively without affecting the validity of the model on the physical level; thirdly a preliminary calculation for nanomaterials’ (...) energy is implemented based on the theory of surface fitting; finally, an integrated framework of nanomaterials modeling, simulation, and visualization is designed and implemented. Experimental results show that the proposed approach is feasible and effective. (shrink)

We outline fresh findings that show that our macroscopic electrocorticographic (ECoG) simulations can account for synchronous multiunit pulse oscillations at separate, simultaneously activated cortical sites and the associated gamma-band ECoG activity. We clarify our views on the approximations of dynamic class applicable to neural events at macroscopic and microscopic scales, and the analogies drawn to classes of ANN behaviour. We accept the need to introduce memory processes and detailed anatomical and physiological information into any future developments of our (...) simulations. On the issue of intrinsic cortical stability and the role of extrinsic fibre systems in maintaining stability, we argue that this position is not in extreme contradiction to those of our commentators, and that the mechanisms implicit in our simulations' properties imply rich computational possibilities. We discuss some of the reasons for and against the existence of significant global resonances in the brain and explain why such behaviour appears absent in our simulations. Last, we discuss other phenomena, such as rhythmic driving of the cortex, which have not yet been introduced into our models, and indicate lines for future development of the simulations. (shrink)

Benveniste’s experiments were at the origin of a scientific controversy that has never been satisfactorily resolved. Hypotheses based on modifications of water structure that were proposed to explain these experiments were generally considered as quite improbable. In the present paper, we show that Benveniste’s experiments violated the law of total probability, one of the pillars of classical probability theory. Although this could suggest that quantum logic was at work, the decoherence process is however at first sight an obstacle to describe (...) this macroscopic experimental situation. Based on the principles of a personalist view of probability, a modeling could nevertheless be built that fitted the outcomes reported in Benveniste’s experiments. Indeed, in QBism, there is no split between microscopic and macroscopic, but between the world where an agent lives and his internal experience of that world. The outcome of an experiment is thus displaced from the object to its perception by an agent. By taking into account both the personalist view of probability and measurement fluctuations, all characteristics of Benveniste’s experiments could be described in a simple modeling: change of the biological system from resting state to “activated” state, concordance of “expected” and observed outcomes and apparent “jumping” of “biological activities” from sample to sample. No hypothesis on change of water structure was necessary. In conclusion, a modeling of Benveniste’s experiments based on a personalist view of probability offers for the first time a logical framework for these experiments that have remained controversial and paradoxical till date. (shrink)

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge from (...) the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline. (shrink)

When can macroscopic data about a system be used to set parameters in a microfoundational simulation? We examine the epistemic viability of tweaking parameter values to generate a better fit between the outcome of a simulation and the available observational data. We restrict our focus to microfoundational simulations—those simulations that attempt to replicate the macrobehavior of a target system by modeling interactions between microentities. We argue that tweaking can be effective but that there are two central risks. First, (...) tweaking risks overfitting the simulation to the data and thus compromising predictive accuracy; and second, it risks compromising the microfoundationality of the simulation. We evaluate standard responses to tweaking and propose strategies to guard against these risks. (shrink)

This paper examines a fundamental problem in applied mathematics. How can one model the behavior of materials that display radically different, dominant behaviors at different length scales. Although we have good models for material behaviors at small and large scales, it is often hard to relate these scale-based models to one another. Macroscale models represent the integrated effects of very subtle factors that are practically invisible at the smallest, atomic, scales. For this reason it has been notoriously difficult to model (...) realistic materials with a simple bottom-up-from-the-atoms strategy. The widespread failure of that strategy forced physicists interested in overall macro-behavior of materials toward completely top-down modeling strategies familiar from traditional continuum mechanics. The problem of the ``tyranny of scales'' asks whether we can exploit our rather rich knowledge of intermediate micro- scale behaviors in a manner that would allow us to bridge between these two dominant methodologies. Macroscopic scale behaviors often fall into large common classes of behaviors such as the class of isotropic elastic solids, characterized by two phenomenological parameters---so-called elastic coefficients. Can we employ knowledge of lower scale behaviors to understand this universality---to determine the coefficients and to group the systems into classes exhibiting similar behavior? (shrink)

As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an (...) explanation of this emergence. With the benefit of hindsight, one can find three periods in the methodologies of modeling in the empirical sciences: 1st the simple modeling of the simple, 2nd the simple modeling of the complex, 3rd the complex modeling and simulation of the complex. Our main thesis is that the current spreading (since the 90’s) of complex computer simulations of systems of models (where a simulation is no more a step by step calculus of a unique logico-mathematical model) is another promising dimension of the science of complexity. Following this claim, we propose to distinguish three different types of computer simulations in the context of complex systems’ modeling. Finally, we show that these types of simulations lead to three different types of weak emergence, too. (shrink)

This paper argues that humans possess unique cognitive abilities due to the presence of a functional system that exists in the human brain that is absent in the non-human brain. This system, the frontal feedback system, was born in the hominin brain when the great phylogenetic expansion of the prefrontal cortex relative to posterior sensory regions surpassed a critical threshold. Surpassing that threshold effectively reversed the preferred direction of information flow in the highest association regions of the neocortex, producing the (...) frontal feedback system. This reversal was from the caudo-rostral bias characteristic of non-human, or pre-human, brain dynamics to a rostro-caudal bias characteristic of modern human brain dynamics. The frontal feedback system works through frontal motor routines, or action schemes, manipulating the release and reconstruction of stored sensory memories in posterior sensory areas. As an obligatory feature of frontal feedback, a central character, or self, emerges within this cortical network that manifests itself as agent in these reconstructions as well as in the experience of sensory perceptions. Dynamical-systems modeling of cortical interactions is combined in the paper with recent neuroimaging studies of “resting-state” brain activity to bridge the gap between microscopic and macroscopic levels of cortical behavior. This synthesis is used to support the proposal of an information flow reversal occurring in the hominin brain and also to explain how such a reversal generates the wide variety of cognitive and experiential phenomena that many consider to be uniquely human. (shrink)

Since the introduction of mathematical population genetics, its machinery has shaped our fundamental understanding of natural selection. Selection is taken to occur when differential fitnesses produce differential rates of reproductive success, where fitnesses are understood as parameters in a population genetics model. To understand selection is to understand what these parameter values measure and how differences in them lead to frequency changes. I argue that this traditional view is mistaken. The descriptions of natural selection rendered by population genetics models are (...) in general neither predictive nor explanatory and introduce avoidable conceptual confusions. I conclude that a correct understanding of natural selection requires explicitly causal models of reproductive success. *Received May 2006; revised December 2006. †To contact the author, please write to: Department of Philosophy, Kansas State University, 201 Dickens Hall, Manhattan, KS 66506; e‐mail: [email protected] . (shrink)

The question of observability of sign changes under 2pi rotations is considered. It is shown that in certain circumstances there are observable consequences of such sign changes in classical physics. A macroscopic experiment is proposed which could in principle detect the 4pi periodicity of rotations.

A macroscopic experiment capable of detecting a signature of spinorial sign changes is discussed. If realized, it would determine whether Bell inequalities are satisfied for a manifestly local, classical system. By providing an explicitly local-realistic derivation of the EPR-Bohm type spin correlations, it is demonstrated why Bell inequalities must be violated even in such a manifestly local, macroscopic domain, just as strongly as they are in the microscopic domain. The proposed experiment has the potential to transform our understanding (...) of the relationship between classical and quantum physics. (shrink)

I show in this paper why the universality of quantum mechanics at all scales, which implies the possibility of Schrodinger's Cat and Wigner's Friend thought experiments, cannot be experimentally confirmed, and why macroscopic superpositions in general cannot be observed or measured, even in principle. Through the relativity of quantum superposition and the transitivity of correlation, it is shown that from the perspective of an object that is in quantum superposition relative to a macroscopic measuring device and observer, the (...) observer is already sufficiently well correlated to the measuring device that once the object correlates to the measuring device, there is no time period in which the observer can perform an appropriate interference experiment to show that the measuring device is in a superposition. (shrink)

Simon Saunders and David Wallace have proposed an attractive semantics for interpreting linguistic communities embedded in an Everettian multiverse. It provides a charitable interpretation of our ordinary talk about the future, and allows us to retain a principle of bivalence for propositions and to retain the law of excluded middle in the logic of propositions about the future. But difficulties arise when it comes to providing an appropriate account of the metaphysics of macroscopic objects and events. I evaluate various (...) metaphysical frameworks which might be combined with the Saunders–Wallace semantics. I conclude that the most appropriate metaphysics to underwrite the semantics renders Everettian quantum mechanics a theory of non-overlapping worlds. (shrink)

Possibility semantics offers an elegant framework for a semantic analysis of modal logic that does not recruit fully determinate entities such as possible worlds. The present papers considers the application of possibility semantics to the modeling of the indeterminacy of the future. Interesting theoretical problems arise in connection to the addition of object-language determinacy operator. We argue that adding a two-dimensional layer to possibility semantics can help solve these problems. The resulting system assigns to the two-dimensional determinacy operator a (...) well-known logic (coinciding with the logic of universal modalities under global consequence). The paper concludes with some preliminary inroads into the question of how to distinguish two-dimensional possibility semantics from the more established branching framework. (shrink)

A macroscopic experiment capable of detecting a signature of spinorial sign changes is discussed. If realized, it would determine whether Bell inequalities are satisfied for a manifestly local, classical system. By providing an explicitly local-realistic derivation of the EPR-Bohm type spin correlations, it is demonstrated why Bell inequalities must be violated even in such a manifestly local, macroscopic domain, just as strongly as they are in the microscopic domain. The proposed experiment has the potential to transform our understanding (...) of the relationship between classical and quantum physics. (shrink)

In a recent arXiv preprint Richard Gill has criticized an experimental proposal published in a journal of theoretical physics which describes how to detect a macroscopic signature of fermionic sign changes. Here I point out that his worries stem from his own elementary algebraic and conceptual mistakes, and present several event-by-event numerical simulations which expose the vacuity of his claims by explicit computations.

Why do we not see large macroscopic objects in entangled states? There are two ways to approach this question. The first is dynamic. The coupling of a large object to its environment cause any entanglement to decrease considerably. The second approach, which is discussed in this paper, puts the stress on the difficulty of observeing a large-scale entanglement. As the number of particles n grows we need an ever more precise knowledge of the state and an ever more carefully (...) designed experiment, in order to recognize entanglement. To develop this point we consider a family of observables, called witnesses, which are designed to detect entanglement. A witness W distinguishes all the separable (unentangled) states from some entangled states. If we normalize the witness W to satisfy tr W 1 for all separable states , then the efficiency of W depends on the size of its maximal eigenvalue in absolute value; that is, its operator norm W . It is known that there are witnesses on the space of n qubits for which W is exponential in n. However, we conjecture that for a large majority of n-qubit witnesses W O n log n . Thus, in a nonideal measurement, which includes errors, the largest eigenvalue of a typical witness lies below the threshold of detection. We prove this conjecture for the family of extremal witnesses introduced by Werner and Wolf [Phys. Rev. A 64, 032112 (2001)]. (shrink)

Modeling is an important scientific practice, yet it raises significant philosophical puzzles. Models are typically idealized, and they are often explored via imaginative engagement and at a certain “distance” from empirical reality. These features raise questions such as what models are and how they relate to the world. Recent years have seen a growing discussion of these issues, including a number of views that treat modeling in terms of indirect representation and analysis. Indirect views treat the model as (...) a bona fide object, specified by the modeler and used to represent and reason about some portion of the concrete empirical world. On some indirect views, model systems are abstract entities, such as mathematical structures, while on other views they are concrete hypothetical things. Here I assess these views and offer a novel account of models. I argue that regarding models as abstracta results in some significant tensions with the practice of modeling, especially in areas where non-mathematical models are common. Furthermore, viewing models as concrete hypotheticals raises difficult questions about model-world relations. The view I argue for treats models as direct, albeit simplified, representations of targets in the world. I close by suggesting a treatment of model-world relations that draws on a recent work by Stephen Yablo concerning the notion of partial truth. (shrink)

This book is about matter. It involves our ordinary concept of matter in so far as this deals with enduring continuants that stand in contrast to the occurrents or processes in which they are involved, and concerns the macroscopic realm of middle-sized objects of the kind familiar to us on the surface of the earth and their participation in medium term processes. The emphasis will be on what science rather than philosophical intuition tells us about the world, and on (...) chemistry rather than the physics that is more usually encountered in philosophical discussions. It is the everyday science of matter characterised by differences of chemical substance that constitutes individuated macroscopic bodies of geological and biological complexity—the continuous matter of macroscopic theory and described by mass terms. -/- The discussion might be characterised as descriptive metaphysics, being content, to paraphrase Strawson’s use of the term, to describe the structure of our scientific thought about the actual world. The method in the central chapters dealing with the nature of matter will be to pursue key steps in the historical development of scientific thought about chemical substance and related concepts with a view to tracing the emergence of a systematic ontological interpretation. Aristotle’s and the Stoics’ discussions of elements and mixtures, based on a continuous view of matter, bear some resemblance to modern, macroscopic conceptions and therefore have some interest as precursors to modern views as well as being of conceptual interest in their own right. Some of the issues they raised are still reflected in modern discussions, despite the considerable increase in complexity of the subject. Other ideas, such as the intimate connection between what modern science distinguishes as substance and phase, maintained their grip on the understanding of matter until the end of the eighteenth century. These are some of the important aspects of the properties of matter that have been neglected by linguistic concerns that have dominated the recent study of mass terms and which the present study seeks to redress. It will be of interest to see how the bounds of possibility are delimited by the laws governing the appropriate use of concepts refined for the purpose of describing the behaviour of matter. But the concern with modality will not stretch to venturing into the realms of metaphysical possibility governed by philosophical speculation about individual essences and underlying natures. -/- Like many contemporary discussions of material objects, this one relies heavily on mereology. Unlike several such discussions, this one adheres to the classical principles of mereology governing the usual dyadic relations of part, overlapping, etc. and the operations of sum, product and difference. These principles apply to the mereological structure of regions of space, intervals of time, processes and quantities of matter. Material objects that gain and lose matter are not understood to gain and lose parts and don’t call for a modification of the classic dyadic mereological relations to triadic relations with the introduction of a third term referring to time. Rather, a distinction is drawn between quantities of matter, which don’t gain or lose parts over time, and individuals, which are typically constituted of different quantities of matter at different times. The proper treatment of the temporal aspect of the features of material objects is a central issue in this book. The topics falling under this heading are addressed by investigating the conditions governing the application of predicates relating time and other entities. Of particular interest here are relations between quantities of matter and times expressing substance kind, phase and mixture. (shrink)

Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces. For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility (...) of models to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written without programming guidelines, makes it almost impossible to access, check, explore, re-use, or continue to develop. It is high time to change this situation, especially since the tools are now readily available to do so. We propose that the modeling community adopt three simple guidelines that would ensure that computational models would be accessible to the broad range of researchers in cognitive science. We further emphasize the pivotal role that journal editors must play in making computational models accessible to readers of their journals. (shrink)

Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in (...) for a physically different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

This paper takes up issues related to the notion of chemical substances arising from their mereological and modal features. Related notions are elements and compounds, into which substances are sub-divided, and the general notion of mixture, which as a special case might involve several substances, but covers other cases too. These are essentially macroscopic concepts. Some of the chemical arguments for this claim have been presented elsewhere. The present paper is a metaphysical treatment of matter as categorised by the (...) major chemical concepts bearing on distinctions between homogeneous and heterogeneous matter, and between a single and several substances. (shrink)

PurposeThis study aims to investigate the impact of perceived service quality on tourist satisfaction and behavioral intentions and explore the potential mediating role of tourist satisfaction in the relationship between service quality and behavioral intentions in the yoga tourism context during the COVID-19 pandemic. Further, this is to examine to what extent yoga tourist satisfaction directly affects their behavioral intentions.Design/methodology/approachBased on a review of literature, the study proposes a conceptual model to test four hypothesized relationships among the constructs of perceived (...) service quality, tourist satisfaction, and behavioral intentions. Data was collected by using a self-administrated questionnaire that was developed and directed to a convenience sample of yoga tourists. Structural equation modeling was employed to determine the relationship between study constructs.FindingsThe results of SEM illustrated that all the hypothesized relationships are supported. The findings confirm that yoga tourists’ behavioral intentions are significantly affected directly and indirectly by perceived service quality. Additionally, tourist satisfaction significantly partially mediates the relationship between PSQ and tourists’ behavioral intentions.Research limitationsThe subject of this study was yoga tourists staying in yoga retreats/studios in Egyptian destinations. Future research... (shrink)

For any choice of initial state and weak assumptions about the Hamiltonian, large isolated quantum systems undergoing Schrödinger evolution spend most of their time in macroscopic superposition states. The result follows from von Neumann’s 1929 Quantum Ergodic Theorem. As a specific example, we consider a box containing a solid ball and some gas molecules. Regardless of the initial state, the system will evolve into a quantum superposition of states with the ball in macroscopically different positions. Thus, despite their seeming (...) fragility, macroscopic superposition states are ubiquitous consequences of quantum evolution. We discuss the connection to many worlds quantum mechanics. (shrink)

We describe here a series of experimental analogies between fluid mechanics and quantum mechanics recently discovered by a team of physicists. These analogies arise in droplet systems guided by a surface (or pilot) wave. We argue that these experimental facts put ancient theoretical work by Madelung on the analogy between fluid and quantum mechanics into new light. After re-deriving Madelung’s result starting from two basic fluid-mechanical equations (the Navier-Stokes equation and the continuity equation), we discuss the relation with the de (...) Broglie-Bohm theory. This allows to make a direct link with the droplet experiments. It is argued that the fluid-mechanical interpretation of quantum mechanics, if it can be extended to the general N-particle case, would have an advantage over the Bohm interpretation: it could rid Bohm’s theory of its strongly non-local character. (shrink)

In this paper I argue that causation is an essentially macroscopic phenomenon, and that mental causes are therefore capable of outcompeting their more specific physical realizers as causes of physical effects. But I also argue that any causes must be type-identical with physical properties, on pain of positing inexplicable physical conspiracies. I therefore allow macroscopic mental causation, but only when it is physically reducible.

It is largely acknowledged that natural languages emerge not just from human brains but also from rich communities of interacting human brains (Senghas, ). Yet the precise role of such communities and such interaction in the emergence of core properties of language has largely gone uninvestigated in naturally emerging systems, leaving the few existing computational investigations of this issue at an artificial setting. Here, we take a step toward investigating the precise role of community structure in the emergence of linguistic (...) conventions with both naturalistic empirical data and computational modeling. We first show conventionalization of lexicons in two different classes of naturally emerging signed systems: (a) protolinguistic “homesigns” invented by linguistically isolated Deaf individuals, and (b) a natural sign language emerging in a recently formed rich Deaf community. We find that the latter conventionalized faster than the former. Second, we model conventionalization as a population of interacting individuals who adjust their probability of sign use in response to other individuals' actual sign use, following an independently motivated model of language learning (Yang, , ). Simulations suggest that a richer social network, like that of natural (signed) languages, conventionalizes faster than a sparser social network, like that of homesign systems. We discuss our behavioral and computational results in light of other work on language emergence, and other work of behavior on complex networks. (shrink)

Aristotelian ideas are presented in a favorable light in Duhem's historical works surveying the history of the notion of chemical combination (1902) and the development of mechanics (1903). The importance Duhem was later to ascribe to Aristotelian ideas as reflected in the weight he attached to medieval science is well known. But the Aristotelian influence on his own mature philosophical perspective, and more particularly on his concern for logical coherence and the development of his ontological views, is not generally acknowledged. (...) There are, however, clear pointers in this direction in these two earlier books on the history of science, which are unashamedly written in such a way as to project the author's own view of what is important in the relevant areas. Thermodynamics was the pinnacle of Duhemian science, and its interpretation requires the reinstatement, in Duhem's view, of Aristotelian conceptions which have been unfashionable since the rise of certain ideas with the scientific revolution of the seventeenth century. The present paper is not primarily an exposition of these Aristotelian views of Duhem's, but an attempt to pursue the interpretation of a macroscopic, thermodynamical perspective on chemical substances from an elementary viewpoint in the spirit of Duhem (1902), sometimes being more definite than Duhem seems to be, and occasionally taking issue with him on certain points. Some of his leading ideas will determine the general approach, but views and problems will also be taken from modern textbooks in an attempt to lay down the general lines along which an explicit ontology--in Quine's sense--of macroscopic theory might be developed. (shrink)

Two strategies for using a model as “null” are distinguished. Null modeling evaluates whether a process is causally responsible for a pattern by testing it against a null model. Baseline modeling measures the relative significance of various processes responsible for a pattern by detecting deviations from a baseline model. When these strategies are conflated, models are illegitimately privileged as accepted until rejected. I illustrate this using the neutral theory of ecology and draw general lessons from this case. First, (...) scientists cannot draw certain conclusions using null modeling. Second, these conclusions follow using baseline modeling, but doing so requires more evidence. (shrink)

Optimization models have often been useful in attempting to understand the adaptive significance of behavioral traits. Originally such models were applied to isolated aspects of behavior, such as foraging, mating, or parental behavior. In reality, organisms live in complex, ever-changing environments, and are simultaneously concerned with many behavioral choices and their consequences. This target article describes a dynamic modeling technique that can be used to analyze behavior in a unified way. The technique has been widely used in behavioral studies (...) of insects, fish, birds, mammals, and other organisms. The models use biologically meaningful parameters and variables, and lead to testable predictions. Limitations arise because nature's complexity always exceeds our modeling capacity. (shrink)

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use. The strong use of an optimality model involves the claim that selection (...) is the only important influence on the evolutionary outcome in question and is thus linked to adaptationism. However, biologists seldom intend this strong use of optimality models. One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome. This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology. The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism. (shrink)

The Lotka–Volterra predator-prey-model is a widely known example of model-based science. Here we reexamine Vito Volterra’s and Umberto D’Ancona’s original publications on the model, and in particular their methodological reflections. On this basis we develop several ideas pertaining to the philosophical debate on the scientific practice of modeling. First, we show that Volterra and D’Ancona chose modeling because the problem in hand could not be approached by more direct methods such as causal inference. This suggests a philosophically insightful (...) motivation for choosing the strategy of modeling. Second, we show that the development of the model follows a trajectory from a “how possibly” to a “how actually” model. We discuss how and to what extent Volterra and D’Ancona were able to advance their model along that trajectory. It turns out they were unable to establish that their model was fully applicable to any system. Third, we consider another instance of model-based science: Darwin’s model of the origin and distribution of coral atolls in the Pacific Ocean. Darwin argued more successfully that his model faithfully represents the causal structure of the target system, and hence that it is a “how actually” model. (shrink)

Bodies as conceived in macroscopic theories are loosely spoken of as participating in processes. But are there any systematic reasons for regarding processes as part of the ontology of macroscopic theory? The present paper suggests that suitable motivation can be found within a project of describing a phenomenological, macroscopic ontology for equilibrium thermodynamics, and outlines some aspects of the interrelation between continuant bodies and processes.

Naturalistic theories of representation seek to specify the conditions that must be met for an entity to represent another entity. Although these approaches have been relatively successful in certain areas, such as communication theory or genetics, many doubt that they can be employed to naturalize complex cognitive representations. In this essay I identify some of the difficulties for developing a teleosemantic theory of cognitive representations and provide a strategy for accommodating them: to look into models of signaling in evolutionary game (...) theory. I show how these models can be used to formulate teleosemantics and expand it in new directions. (shrink)

MaxEnt inference algorithm and information theory are relevant for the time evolution of macroscopic systems considered as problem of incomplete information. Two different MaxEnt approaches are introduced in this work, both applied to prediction of time evolution for closed Hamiltonian systems. The first one is based on Liouville equation for the conditional probability distribution, introduced as a strict microscopic constraint on time evolution in phase space. The conditional probability distribution is defined for the set of microstates associated with the (...) set of phase space paths determined by solutions of Hamilton’s equations. The MaxEnt inference algorithm with Shannon’s concept of the conditional information entropy is then applied to prediction, consistently with this strict microscopic constraint on time evolution in phase space. The second approach is based on the same concepts, with a difference that Liouville equation for the conditional probability distribution is introduced as a macroscopic constraint given by a phase space average. We consider the incomplete nature of our information about microscopic dynamics in a rational way that is consistent with Jaynes’ formulation of predictive statistical mechanics, and the concept of macroscopic reproducibility for time dependent processes. Maximization of the conditional information entropy subject to this macroscopic constraint leads to a loss of correlation between the initial phase space paths and final microstates. Information entropy is the theoretic upper bound on the conditional information entropy, with the upper bound attained only in case of the complete loss of correlation. In this alternative approach to prediction of macroscopic time evolution, maximization of the conditional information entropy is equivalent to the loss of statistical correlation, and leads to corresponding loss of information. In accordance with the original idea of Jaynes, irreversibility appears as a consequence of gradual loss of information about possible microstates of the system. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. (...) Moreover, we argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)