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Mathematics plays a central role in much of contemporary science, but philosophers have struggled to understand what this role is or how significant it might be for mathematics and science. Pincock tackles this perennial question by asking how mathematics contributes to the success of our best scientific representations.
This monograph offers a critical introduction to current theories of how scientific models represent their target systems. Representation is important because it allows scientists to study a model to discover features of reality. The authors provide a map of the conceptual landscape surrounding the issue of scientific representation, arguing that it consists of multiple intertwined problems. They provide an encyclopaedic overview of existing attempts to answer these questions, and they assess their strengths and weaknesses. The book also presents a comprehensive statement of their alternative proposal, the DEKI account of representation, which they have developed over the last few years. They show how the account works in the case of material as well as non-material models; how it accommodates the use of mathematics in scientific modelling; and how it sheds light on the relation between representation in science and art. The issue of representation has generated a sizeable literature, which has been growing fast in particular over the last decade. This makes it hard for novices to get a handle on the topic because so far there is no book-length introduction that would guide them through the discussion. Likewise, researchers may require a comprehensive review that they can refer to for critical evaluations. This book meets the needs of both groups.
This volume assembles cutting-edge scholarship on scientific understanding, scientific representation, and their delicate interplay. Featuring several articles in an engaging ‘critical conversation’ format, the volume integrates discussions about understanding and representation with perennial issues in the philosophy of science, including the nature of scientific knowledge, idealizations, scientific realism, scientific inference, and scientific progress. In the philosophy of science, questions of scientific understanding and scientific representation have only recently been put in dialogue with each other. The chapters advance these discussions from a variety of fresh perspectives. They range from case studies in physics, chemistry, and neuroscience to the representational challenges of machine learning models; from special forms of representation such as maps and topological models to the relation between understanding and explanation; and from the role of idealized representations to the role of representation and understanding in scientific progress. Scientific Understanding and Representation will appeal to scholars and advanced students working in philosophy of science, philosophy of physics, philosophy of mathematics, and epistemology.
Over the course of his distinguished career, Nicolai Reshetikhin has made a number of groundbreaking contributions in several fields, including representation theory, integrable systems, and topology. The chapters in this volume – compiled on the occasion of his 60th birthday – are written by distinguished mathematicians and physicists and pay tribute to his many significant and lasting achievements. Covering the latest developments at the interface of noncommutative algebra, differential and algebraic geometry, and perspectives arising from physics, this volume explores topics such as the development of new and powerful knot invariants, new perspectives on enumerative geometry and string theory, and the introduction of cluster algebra and categorification techniques into a broad range of areas. Chapters will also cover novel applications of representation theory to random matrix theory, exactly solvable models in statistical mechanics, and integrable hierarchies. The recent progress in the mathematical and physicals aspects of deformation quantization and tensor categories is also addressed. Representation Theory, Mathematical Physics, and Integrable Systems will be of interest to a wide audience of mathematicians interested in these areas and the connections between them, ranging from graduate students to junior, mid-career, and senior researchers.
This Element presents a philosophical exploration of the notion of scientific representation. It does so by focussing on an important class of scientific representations, namely scientific models. Models are important in the scientific process because scientists can study a model to discover features of reality. But what does it mean for something to represent something else? This is the question discussed in this Element. The authors begin by disentangling different aspects of the problem of representation and then discuss the dominant accounts in the philosophical literature: the resemblance view and inferentialism. They find them both wanting and submit that their own preferred option, the so-called DEKI account, not only eschews the problems that beset these conceptions, but further provides a comprehensive answer to the question of how scientific representation works. This title is also available as Open Access on Cambridge Core.
This book analyzes Bas van Fraassen’s characterization of representation and models in science. In this regard, it presents the philosophical coordinates of his approach and pays attention to his structural empiricism as a framework for his views on scientific representations and models. These are developed here through two new contributions made by van Fraassen. In addition, there are analyses of the relation between models and reality in his approach, where the complexity of this conception is considered in detail. Furthermore, there is an examination of scientific explanation and epistemic values judgments. This volume includes a wealth of bibliographical information on his philosophy and relevant philosophical issues. Bas van Fraassen is a key figure in contemporary philosophy of science, as the prestigious Hempel Award shows. His views on scientific representation offer new ideas on how it should be characterized, and his conception of models shows a novelty that goes beyond other empiricists’ approaches of recent times. Both aspects — the characterization of scientific representation and the conception of models in science — are part of a deliberate attempt to forge a “structural empiricism,” an alternative to structural realism based on an elaborated version of empiricism.
Author : Patrick Suppes Publisher : Stanford Univ Center for the Study Page : 536 pages File Size : 43,74 MB Release : 2002 Category : Science ISBN : 9781575863337
A fundamental reason for using formal methods in the philosophy of science is the desirability of having a fixed frame of reference that may be used to organize the variety of doctrines at hand. This book—Patrick Suppes's major work, and the result of several decades of research—examines how set-theoretical methods provide such a framework, covering issues of axiomatic method, representation, invariance, probability, mechanics, and language, including research on brain-wave representations of words and sentences. This is a groundbreaking, essential text from a distinguished philosopher.
In this dissertation, I consider from a philosophical perspective three related questions concerning the contribution of mathematics to scientific representation. In answering these questions, I propose and defend Carnapian frameworks for examination into the nature and role of mathematics in science. The first research question concerns the varied ways in which mathematics contributes to scientific representation. In response, I consider in Chapter 2 two recent philosophical proposals claiming to account for the explanatory role of mathematics in science, by Philip Kitcher, and Otavio Bueno and Mark Colyvan. My novel and detailed critique of these accounts shows that they are too limited to encompass the diverse roles of mathematics in science in historical and contemporary scenarios. The conclusion is that any such philosophical account should aim to faithfully capture the structure of our theories and their use in applied contexts. This insight prompts the second question guiding this dissertation that I consider in Chapter 3, regarding a viable philosophical account of the role of mathematics in scientific theories. I respond by proposing a modified form of the reconstructive frameworks for philosophical analysis developed by Rudolf Carnap for theoretical entities. I propose three amendments to Carnap's account: i) a semantic view for the representation of theories, ii) a careful consideration of instances of the use of theory in representing target systems, and iii) consideration of the practical complexity of relating theory to experimental data. The final research question for this dissertation asks what, if anything, we can legitimately conclude about the nature of theoretical entities invoked by a theory in light of its success in representing phenomena. In the backdrop of the Carnapian frameworks proposed in Chapter 3, I argue that contemporary ontological debates in the philosophy of science are largely premised on an acceptance of Willard Quine's epistemological outlook on the world and a dismissal of Carnap's approach, which can be used to offer a satisfactory deflationary resolution. This is in the service of my contention that a Carnapian attitude to central issues in the philosophy of science is decidedly preferable to the route championed by Quine.
External representations (pictures, diagrams, graphs, concrete models) have always been valuable tools for the science teacher. This book brings together the insights of practicing scientists, science education researchers, computer specialists, and cognitive scientists, to produce a coherent overview. It links presentations about cognitive theory, its implications for science curriculum design, and for learning and teaching in classrooms and laboratories.