Reductionist and anti-reductionist perspectives on dynamics (original) (raw)

Reductionist and Antireductionist

In this paper reduction and its pragmatics are discussed in the light of the development in Computer Science of languages to describe processes. The design of higher-level description languages within Computer Science has had the aim of allowing for description of the dynamics of processes in the (physical) world on a higher level avoiding all (physical) details of these processes. The higher description levels developed have dramatically increased the complexity of applications that came within reach. The pragmatic attitude of a (scientific) practitioner in this area has become inherently anti-reductionist, but based on well-established reduction relations. The paper discusses how this perspective can be related to reduction in general, and to other domains where description of dynamics plays a main role, in particular, biological and cognitive domains.

Reduction in Dynamical Systems: A Representational View

2010

ABSTRACT: According to the received view, reduction is a deductive relation between two formal theories. In this paper, I develop an alternative approach, according to which reduction is a representational relation between models, rather than a deductive relation between theories; more specifically, I maintain that this representational relation is the one of emulation. To support this thesis, I focus attention on mathematical dynamical systems and I argue that, as far as these systems are concerned, the emulation relation is sufficient for reduction. I then extend this representational view of reduction to the case of empirically interpreted dynamical systems, as well as to a treatment of partial, approximate, and asymptotic reduction.

A Representational Approach to Reduction in Dynamical Systems

Erkenntnis, 79(4):943-968, 2014

According to the received view, reduction is a deductive relation between two formal theories. In this paper, I develop an alternative approach, according to which reduction is a representational relation between models, rather than a deductive relation between theories; more specifically, I maintain that this representational relation is the one of emulation. To support this thesis, I focus attention on mathematical dynamical systems and I argue that, as far as these systems are concerned, the emulation relation is sufficient for reduction. I then extend this representational model-based view of reduction to the case of empirically interpreted dynamical systems, as well as to a treatment of partial, approximate, and asymptotic reduction.

Reductionism and its heuristics: Making methodological reductionism honest

Synthese, 2006

Methodological reductionists practice 'wannabe reductionism'. They claim that one should pursue reductionism, but never propose how. I integrate two strains in prior work to do so. Three kinds of activities are pursued as "reductionist". "Successional reduction" and inter-level mechanistic explanation are legitimate and powerful strategies. Eliminativism is generally ill-conceived. Specific problem-solving heuristics for constructing inter-level mechanistic explanations show why and when they can provide powerful and fruitful tools and insights, but sometimes lead to erroneous results. I show how traditional metaphysical approaches fail to engage how science is done. The methods used do so, and support a pragmatic and non-eliminativist realism.

The problem of reductionism from a system theoretical viewpoint

Journal for General Philosophy of Science - Zeitschrift für Allgemeine Wissenschaftstheorie, 1983

Inspite of the great success in many disciplines the program of reductionism has failed its genuine purpose. Systemtheory however has yielded a new concept of reducfionism which we call reductionism by correspondence and which may imply a new understanding of the mind-body problem. The crucial operations of reductionism by correspondence are called idealization, interpretation and classification. They are used to optimize the description of a system. Nevertheless they lead to certain deficiencies which cannot be avoided in principle. We are therefore driven to the assumption that natural systems can only be described as probabilistic systems. From this point of view nothing is said about the direction of the reduction.

A compromise between reductionism and non-reductionism

Worldviews, science and us: philosophy and …, 2007

This paper investigates the seeming incompatibility of reductionism and nonreductionism in the context of complexity sciences. I review algorithmic information theory for this purpose. I offer two physical metaphors to form a better understanding of algorithmic complexity, and I briefly discuss its advantages, shortcomings and applications. Then, I revisit the non-reductionist approaches in philosophy of mind which are often arguments from ignorance to counter physicalism. A new approach called mild non-reductionism is proposed which reconciliates the necessities of acknowledging irreducibility found in complex systems, and maintaining physicalism.

The New Reductionism 1

The Philosophical Forum, 2008

have developed a form of reductionism, based on advances in quantum physics that is radically different from any type of reductionism discussed by philosophers. Gell-Mann and the Santa Fe Institute have instituted a program for studying complexity and emergence. Both programs undercut presuppositions about the role of physics that are implicitly shared by both reductionists and emergentists. Yet, this work has received virtually no serious consideration from philosophers writing about these issues. Three basic reasons may be assigned for this neglect. First, the reductionist program was originally developed in highly technical papers concerned with the consistent histories interpretation of quantum mechanics and its application to quantum cosmology. The treatment of emergence was developed through a series of specialized studies on various forms of complexity. Second, the new program focuses on structures and dynamics, rather than on entities and their properties. The study of complex adaptive systems (CAS) includes pre-biotic evolution, forest fires, butterfly patterns, human social behavior, ant colonies, the stock market, and leopard's spots, topics foreign to the traditional philosophical debates. Third, the new reductionism is solidly based on contemporary physics. Current philosophical discussions of global reductionism generally replace physics by a metaphysical doctrine of physicalism. This point requires some clarification. Philosophers commonly distinguish three different types of reductionism: epistemological, concerned with knowledge; methodological, concerned with theories; and ontological, concerned with entities. The reduction/emergence debates generally rely on presuppositions about levels. Even without any generally accepted theory of levels, there is a widespread acceptance of relative levels, for example, particles, atoms, molecules, complex molecules, organic molecules,

Reductionist perspectives and the notion of information

Progress in biophysics and molecular biology, 2016

Reductionism is the dominant stance of biology. According to this perspective, biological phenomena have to fit with physical explanations. Some biologists thought that the introduction of the idea of program was a sound way to overcome both physicalism and reductionism. We argue instead that the introduction of information theory into biology did not liberate biology from reductionism. We argue that the adoption of information in biology is an erroneous transposition from a specific mathematical domain to one where it does not belong. Indeed, the mathematical framework of the information theory is too rigid and discrete to fit with biological phenomena. Therefore, information in biology represents an inappropriate metaphor. Then, we make explicit the use of metaphors and the choice of explanation mode. We argue that the choice of explanation is not neutral. Furthermore, the use of metaphors in science becomes dangerous when they take the place of theories and they lose their parado...

The Limits of Reductionism in the Life Sciences

History and philosophy of the life sciences, 2011

"In the contemporary life sciences more and more researchers emphasize the “limits of reductionism” (e.g. Ahn et al. 2006a, 709; Mazzocchi 2008, 10) or they call for a move “beyond reductionism” (Gallagher/Appenzeller 1999, 79). However, it is far from clear what exactly they argue for and what the envisioned limits of reductionism are. In this paper I claim the current discussions about reductionism in the life sciences, which focus on methodological and explanatory issues, leave the concepts of a reductive method and a reductive explanation too unspecified. In order to fill this gap and to clarify what the limits of reductionism are I identify three reductive methods that are crucial in the current practice of the life sciences: decomposition, focusing on internal factors, and studying parts in isolation (i.e. not in vivo). Furthermore, I argue that reductive explanations in the life sciences exhibit three characteristics: they refer only to factors at a lower level than the phenomenon at issue, they focus on internal factors and thus ignore or simplify the environment of a system, and they cite only the parts of a system in isolation."

Reductionism in Cognitive Science

2012

A description of theoretic and explanatory reductions and their features is followed by an example of epistemic reduction of a model in cognitive psychology to models in computational neuroscience. The paper also aims to visit the notions of implementation, realization and explanation with respect to reduction as they might be relevant. Only epistemic reduction and its features are discussed in order to restrict the scope of this paper though other forms of reduction exist. Opinions on reductions in general are presented in the final section.