We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage (...) and analyze the differential impact of evidence and credence change at different points within a single network and across different theoretical structures. (shrink)

According to the semantic view of scientific theories, theories are classes of models. I show that this view -- if taken seriously as a formal explication -- leads to absurdities. In particular, this view equates theories that are truly distinct, and it distinguishes theories that are truly equivalent. Furthermore, the semantic view lacks the resources to explicate interesting theoretical relations, such as embeddability of one theory into another. The untenability of the semantic view -- as (...) currently formulated -- threatens to undermine scientific structuralism. (shrink)

Churchland proposes a radically new way of representing theories and their acquisition in the terms of connectionist neuro- science. ...

It is plausible that the models of scientific theories correspond to possibilities. But how do we know which models of which scientific theories so correspond? This paper provides a novel proposal for guiding belief about possibilities via scientific theories. The proposal draws on the notion of an effective theory: a theory that applies very well to a particular, restricted domain. We argue that it is the models of effective theories that we should believe (...) correspond, at least in part, to possibilities. It is thus effective theories that should guide modal reasoning in science. (shrink)

This book is about the methods used for unifying different scientific theories under one all-embracing theory. The process has characterized much of the history of science and is prominent in contemporary physics; the search for a 'theory of everything' involves the same attempt at unification. Margaret Morrison argues that, contrary to popular philosophical views, unification and explanation often have little to do with each other. The mechanisms that facilitate unification are not those that enable us to explain how (...) or why phenomena behave as they do. A feature of this book is an account of many case studies of theory unification in nineteenth- and twentieth-century physics and of how evolution by natural selection and Mendelian genetics were unified into what we now term evolutionary genetics. (shrink)

Scientific theories are used for a variety of purposes. For example, physical theories such as classical mechanics and electrodynamics have important applications in engineering and technology, and we trust that this results in useful machines, stable bridges, and the like. Similarly, theories such as quantum mechanics and relativity theory have many applications as well. Beyond that, these theories provide us with an understanding of the world and address fundamental questions about space, time, and matter. Here (...) we trust that the answers scientific theories give are reliable and that we have good reason to believe that the features of the world are similar to what the theories say about them. But why do we trust scientific theories, and what counts as evidence in favor of them? (shrink)

Since the beginning of the 20th century, philosophers of science have asked, "what kind of thing is a scientific theory?" The logical positivists answered: a scientific theory is a mathematical theory, plus an empirical interpretation of that theory. Moreover, they assumed that a mathematical theory is specified by a set of axioms in a formal language. Later 20th century philosophers questioned this account, arguing instead that a scientific theory need not include a mathematical component; or that the (...) mathematical component need not be specified by a set of axioms in a formal language. We survey various accounts of scientific theories entertained in the 20th century -- removing some misconceptions, and clearing a path for future research. (shrink)

This chapter contains sections titled: Introduction The Once Received View (ORV) Criticisms of the ORV The “Model Model” of Scientific Theories Mechanisms: Investigating Nonformal Patterns in Scientific Theories Conclusion.

Is the universe really governed by a small set of unifying fundamental laws, as many thinkers have claimed since ancient times? Philosophers who call themselves naturalists believe that the way to settle such questions is to look carefully at what empirical science tells us. In this book, Margaret Morrison argues that if we really do this, we find that science currently does not give us any reason to believe the common picture of the world in which everything can be reduced (...) to a vanishingly small set of entities and forces. Like Nancy Cartwright and John Dupree, Morrison believes that science reveals a world of numerous different sorts of entities and processes, described by different sorts of explanation. Trying to come up with unified descriptions of phenomena does play an important role in science, says Morrison, but there are different types of unification. The sort in which one set of entities can be reductively identified with another occurs rarely. What we find more often are various ways of subsuming different phenomena under similar mathematical formalisms. An urge to unify, in different guises, is an important research motivator, Morrison argues, but it is not the sort of monolithic engine of science that many make it out to be. (shrink)

Model checking, a prominent formal method used to predict and explain the behaviour of software and hardware systems, is examined on the basis of reflective work in the philosophy of science concerning the ontology of scientific theories and model-based reasoning. The empirical theories of computational systems that model checking techniques enable one to build are identified, in the light of the semantic conception of scientific theories, with families of models that are interconnected by simulation relations. (...) And the mappings between these scientific theories and computational systems in their scope are analyzed in terms of suitable specializations of the notions of model of experiment and model of data. Furthermore, the extensively mechanized character of model-based reasoning in model checking is highlighted by a comparison with proof procedures adopted by other formal methods in computer science. Finally, potential epistemic benefits flowing from the application of model checking in other areas of scientific inquiry are emphasized in the context of computer simulation studies of biological information processing. (shrink)

Thagard's theory of explanatory coherence (TEC) is a conceptual and computational framework that is used to show how new scientific theories can be judged to be superior to previous ones. In Structures in Science (SiS), Kuipers criticizes TEC as a model that does not faithfully reflect scientific practice. This article tries to explain the machinery behind TEC, and tries to indicate where TEC falls short (conceptually speaking) and where it can be improved. The main idea proposed in (...) this article is not to derive a coherence network from the input (à la TEC), but to construct a coherence network right from the input itself. (shrink)

Summary Peter Bowler's account of the biology and social views of E. W. MacBride is to be welcomed. He is correct in saying that the case of MacBride, who was both a Lamarckian and a Right-wing eugenist, ought to remind us that scientific theories bear no intrinsic, logically inherent, political implications. But it would be wholly mistaken to attribute the view that theories do contain such implications to the sociology of scientific knowledge. It is one that (...) no consistent proponent of the sociology of scientific knowledge can or does accept. As Bowler says, and as sociologists of scientific knowledge have long asserted, links between scientific theories and political positions are features of particular social circumstances. These connections can always, in principle, be broken or revised, and in practice they fairly frequently are. (shrink)

The positivistic Received View construed scientific theories syntactically as axiomatic calculi where theoretical terms were given a partial semantic interpretation via correspondence rules connecting them to observation statements. This paper assesses what, with hindsight, seem the most important defects in the Received View; surveys the main proposed successor analyses to the Received View--various Semantic Conception versions and the Structuralist Analysis; evaluates how well they avoid those defects; examines what new problems they face and where the most promising require (...) further development or leave unanswered questions; explores implications of recent work on models for understanding theories; and rebuts the few criticisms of the Semantic Conception that have surfaced. (shrink)

(2013). Is scientific theory change similar to early cognitive development? Gopnik on science and childhood. Philosophical Psychology: Vol. 26, No. 1, pp. 109-128. doi: 10.1080/09515089.2011.625114.

According to the semantic view, a theory is characterized by a class of models. In this paper, we examine critically some of the assumptions that underlie this approach. First, we recall that models are models of something. Thus we cannot leave completely aside the axiomatization of the theories under consideration, nor can we ignore the metamathematics used to elaborate these models, for changes in the metamathematics often impose restrictions on the resulting models. Second, based on a parallel between van (...) Fraassen’s modal interpretation of quantum mechanics and Skolem’s relativism regarding set-theoretic concepts, we introduce a distinction between relative and absolute concepts in the context of the models of a scientific theory. And we discuss the significance of that distinction. Finally, by focusing on contemporary particle physics, we raise the question: since there is no general accepted unification of the parts of the standard model (namely, QED and QCD), we have no theory, in the usual sense of the term. This poses a difficulty: if there is no theory, how can we speak of its models? What are the latter models of? We conclude by noting that it is unclear that the semantic view can be applied to contemporary physical theories. (shrink)

The philosopher of science faces overwhelming disagreement in the literature on the definition, nature, structure, ontology, and content of scientific theories. These disagreements are at least partly responsible for disagreements in many of the debates in the discipline which put weight on the concept scientific theory. I argue that available theories of theories and conceptual analyses of theory are ineffectual options for addressing this difficulty: they do not move debates forward in a significant way. Directing (...) my attention to debates about the properties of particular, named theories, I introduce ‘theory eliminativism’ as a certain type of debate-reformulation. As a methodological tool it has the potential to be a highly effective way to make progress in the face of the noted problem: post-reformulation disagreements about theory cannot compromise the debate, and the questions that really matter can still be asked and answered. In addition the reformulation process demands that philosophers engage with science and the history of science in a more serious way than is usual in order to answer important questions about the justification for targeting a particular set of propositions (say) in a given context. All things considered, we should expect the benefits of a theory-eliminating debate-reformulation to heavily outweigh the costs for a highly significant number of debates of the relevant type. (shrink)

Representative models are considered parts of real scientific theories.

Suppe, F. The search for philosophic understanding of scientific theories (p. [1]-241)--Proceedings of the symposium.--Bibliography, compiled by Rew A. Godow, Jr. (p. [615]-646).

This paper analyzes recent work in psychology on the nature of the representation of complex forms of knowledge with the goal of understanding how theories are represented. The analysis suggests that, as a psychological form of representation, theories are mental structures that include theoretical entities (usually nonobservable), relationships among the theoretical entities, and relationships of the theoretical entities to the phenomena of some domain. A theory explains the phenomena in its domain by providing a conceptual framework for the (...) phenomena that leads to a feeling of understanding in the reader/hearer. The explanatory conceptual framework goes beyond the original phenomena, integrates diverse aspects of the world, and shows how the original phenomena follow from the framework. This analysis is used to argue that mental models are the subclass of theories that use causal/mechanical explanatory frameworks. In addition, an argument is made for a new psychologism in the philosophy of science, in which the mental representation of scientific theories must be taken into account. (shrink)

First, I discuss the older “theory-centered” and the more recent semantic conception of scientific theories. I argue that these two perspectives are nothing more than terminological variants of one another. I then offer a new theory-centered view of scientific theories. I argue that this new view captures the insights had by each of these earlier views, that it’s closer to how scientists think about their own theories, and that it better accommodates the phenomenon of inconsistent (...) scientific theories. (shrink)

The contributions to Testing Scientific Theories are unified by an in-terest in responding to criticisms directed by Glymour against existing models of confirmation—chiefly H-D and Bayesian schemas—and in assessing and correcting the "bootstrap" model of confirmation that he proposed as an alternative in Theory and Evidence (1980). As such, they provide a representative sample of objections to Glymour's model and of the wide range of new initiatives in thinking about scientific confirmation that it has influenced. The effect (...) is a sense of engagement and focus, and of significant advance at least in articulation of the problems that require solution; as Earman observes, "it is . . . heartening to report that the various opposing camps learned from each other" (p. vi).' In what follows I am concerned to assess what has been learned both critically, about Glymour's model, and constructively about the resources of the alternatives he challenges. My thesis is that while the theories emerging in this debate do deal with a wider range of scientific practice than before, their remaining limitations raise important questions about the ambitions and criteria of adequacy that have traditionally governed philosophical inquiry in this area. (shrink)

In this paper some classical representational ideas of Hertz and Duhem are used to show how the dichotomy between representation and intervention can be overcome. More precisely, scientific theories are reconstructed as complex networks of intervening representations (or representational interventions). The formal apparatus developed is applied to elucidate various theoretical and practical aspects of the in vivo/in vitro problem of biochemistry. Moreover, adjoint situations (Galois connections) are used to explain the relation berween empirical facts and theoretical laws in (...) a new way. (shrink)

This book addresses the logical aspects of the foundations of scientific theories. Even though the relevance of formal methods in the study of scientific theories is now widely recognized and regaining prominence, the issues covered here are still not generally discussed in philosophy of science. The authors focus mainly on the role played by the underlying formal apparatuses employed in the construction of the models of scientific theories, relating the discussion with the so-called semantic (...) approach to scientific theories. The book describes the role played by this metamathematical framework in three main aspects: considerations of formal languages employed to axiomatize scientific theories, the role of the axiomatic method itself, and the way set-theoretical structures, which play the role of the models of theories, are developed. The authors also discuss the differences and philosophical relevance of the two basic ways of aximoatizing a scientific theory, namely Patrick Suppes’ set theoretical predicates and the "da Costa and Chuaqui" approach. This book engages with important discussions of the nature of scientific theories and will be a useful resource for researchers and upper-level students working in philosophy of science. (shrink)

Most philosophical accounts on scientific theories are affected by three dogmas or ingrained attitudes. These dogmas have led philosophers to choose between analyzing the internal structure of theories or their historical evolution. In this paper, I turn these three dogmas upside down. I argue (i) that mathematical practices are not epistemically neutral, (ii) that the morphology of theories can be very complex, and (iii) that one should view theoretical knowledge as the combination of internal factors and (...) their intrinsic historicity. (shrink)

The English Synopsis is after the text of the book. The book presents an original and generalizing substantive vision of the philosophy of science through the prism of a detailed analysis of the polysystem structure of scientific theories. Theories are considered, firstly, as complex specialized forms of developed scientific thinking about the realities studied by natural science, secondly, as constantly improving tools for producing new knowledge in interaction with experimental research, and thirdly, as carriers of ordered (...) and verified knowledge. Emphasis is placed on their nominal and ontic subsystems. The book develops personal and joint research of the authors (theoretical physicist and philosopher), the experience of teaching philosophy of physics at NaUKMA, philosophy of science at the Higher School of Philosophy at the H. Skovoroda Institute of Philosophy of the National Academy of Sciences of Ukraine and theoretical physics at the National Technical University "Ihor Sikorsky Kyiv Polytechnic Institute". The research is based on a significant source base covering works of modern Western researchers in natural science and philosophy of science. For students, teachers, and scientists who are interested in the problems of modern philosophy of science and have a certain amount of scientific knowledge. It will also be useful for high school students who are eager to become scientists. (shrink)

In this paper some classical representational ideas of Hertz and Duhem are used to show how the dichotomy between representation and intervention can be overcome. More precisely, scientific theories are reconstructed as complex networks of intervening representations (or representational interventions). The formal apparatus developed is applied to elucidate various theoretical and practical aspects of the in vivo/in vitro problem of biochemistry. Moreover, adjoint situations (Galois connections) are used to explain the relation between empirical facts and theoretical laws in (...) a new way. (shrink)

In what follows, I argue that the semantic approach to scientific theories fails as a means to present the Wright—Fisher formalism (WFF) of population genetics. I offer an account of what population geneticist understand insofar as they understand the WFF, a variation on Lloyd's view that population genetics can be understood as a family of models of mid-level generality.

Rich with historical and cultural value, these works are published unaltered from the original University of Minnesota Press editions.

Scientific inquiry has led to immense explanatory and technological successes, partly as a result of the pervasiveness of scientific theories. Relativity theory, evolutionary theory, and plate tectonics were, and continue to be, wildly successful families of theories within physics, biology, and geology. Other powerful theory clusters inhabit comparatively recent disciplines such as cognitive science, climate science, molecular biology, microeconomics, and Geographic Information Science (GIS). Effective scientific theories magnify understanding, help supply legitimate explanations, and assist (...) in formulating predictions. Moving from their knowledge-producing representational functions to their interventional roles (Hacking 1983), theories are integral to building technologies used within consumer, industrial, and scientific milieus. -/- This entry explores the structure of scientific theories from the perspective of the Syntactic, Semantic, and Pragmatic Views. Each of these views answers questions such as the following in unique ways. What is the best characterization of the composition and function of scientific theory? How is theory linked with world? Which philosophical tools can and should be employed in describing and reconstructing scientific theory? Is an understanding of practice and application necessary for a comprehension of the core structure of a scientific theory? How are these three views ultimately related? (shrink)

Selective scientific realists disagree on which theoretical posits should be regarded as essential to the empirical success of a scientific theory. A satisfactory account of essentialness will show that the (approximate) truth of the selected posits adequately explains the success of the theory. Therefore, (a) the essential elements must be discernible prospectively; (b) there cannot be a priori criteria regarding which type of posit is essential; and (c) the overall success of a theory, or ‘cluster’ of propositions, not (...) only individual derivations, should be explicable. Given these desiderata, I propose a “unification criterion” for identifying essential elements. (shrink)

Attempts by 20th century philosophers of science to define inductive concepts and methods concerning the support provided to scientific theories by empirical data have been unsuccessful. Although 20th century philosophers of science largely ignored statistical methods for testing theories, when they did address them they argued against rather than for their use. In contrast, this study demonstrates that traditional statistical methods used for validating computer simulation models provide tests of the scientific theories that those models (...) may embody. This study shows that these statistical methods are applicable regardless of whether the scientific theory or model is deterministic, stochastic, or chaos-based in nature. Traditional statistical methods, such as hypothesis testing, test theories by providing measures of their goodness-of-fit with the portion of the world the theories describe. Nothing more is needed to portray the agreement between theory and the world. Furthermore, the statistical measures of goodness-of-fit are not ampliative inductive measures. Therefore, the ultimate value and direction of the 20 th century ampliative inductive program within philosophy of science is thrown into question. This study also suggests that advanced statistical, visualization, and hybrid quantitative qualitative methods hold promise for offering scientists additional methods for testing scientific theories through validating their computer model representations. As a prerequisite to the above discussions, this study proves that scientific theories, when applied to concrete physical systems, can indeed be represented by computer models. (shrink)

Question: What is a (or the) scientific theory V based on a set B of syntactical L-formulas, interpreted according to the intended interpretations of the language L? What probably corresponds to the traditional candidate for V is found to be inadequate for use in deductively explaining experimental facts of a certain form. A second candidate for V, called a strong scientific theory (SST), does not suffer such an inadequacy because it is existentially strong, i.e., it has considerable existential (...) import. It even satisfies the particle physicist's dictum: WHAT IS NOT FORBIDDEN WILL HAPPEN. (shrink)

Ernest Barnes was invited to Aberdeen as Gifford Lecturer (1927-1929) to deliver lectures under the title of 'Scientific Theory and Religion'. The lectures were originally published in 1933 and sought to bring Christian doctrines together with the possibility of life on other planets. The magnitude of the universe, accompanied with some basic observations on biological development within it, makes speculation about the possibility of intelligent life in distant galaxies reasonable. Barnes believed that the Creation was made precisely for the (...) higher forms of' consciousness. The scope of the background to scientific theory and religious ideas of creation presented here is extensive and covers topics including Jewish cosmology as the basis for later Christian thought to early quantum mechanics and evolutionary biology. However, as Barnes himself noted of this scope in his lectures, 'Wide as is their range, they have an inner coherence. I trust that they express the attitude of the modern man of science who, as he hopefully makes theories, is aware of the limitations of his knowledge and also, in part because of his loyalty to truth, bears in mind the reality and the claims of the spiritual world.'. (shrink)

We discuss ways in which category theory might be useful in philosophy of science, in particular for articulating the structure of scientific theories. We argue, moreover, that a categorical approach transcends the syntax-semantics dichotomy in 20th century analytic philosophy of science.

Associated with Bayesianism is the claim that insofar as thereis anything like scientific theory-commitment, it is not a doxastic commitment to the truth of the theory or any proposition involving the theory, but is rather an essentiallypractical commitment to behaving in accordance with a theory. While there are a number of a priori reasons to think that this should be true, there is stronga posteriori reason to think that it is not in fact true of current scientific practice.After (...) outlining a feature that distinguishes doxastic from practical commitment, I presentempirical evidence that suggests that, like perhaps all other theoretical commitment,scientific theory-commitment is doxastic. (shrink)

Putnam (1975) infers from the success of a scientific theory to its approximate truth and the reference of its key term. Laudan (1981) objects that some past theories were successful, and yet their key terms did not refer, so they were not even approximately true. Kitcher (1993) replies that the past theories are approximately true because their working posits are true, although their idle posits are false. In contrast, I argue that successful theories which cohere with (...) each other are approximately true, and that their key terms refer. My position is immune to Laudan’s counterexamples to Putnam’s inference and yields a solution to a problem with Kitcher’s position. (shrink)

Since the publication of his seminal monograph "The scientific image", Bas van Fraassen is a key figure in philosophy of science. In this book, other philosophers with various outlooks critically discuss his work on theories, empiricism and philosophical stances. The book starts with a new article by van Fraassen on his preferred account of theories, the so-called semantic view. This account is now 50 years old, and van Fraassen takes this anniversary as an opportunity to review the (...) account, its history and the philosophical discussion about it. In the main part of the book, Nancy Cartwright, Finnur Dellsén, Matthias Egg, Steven French, Michael Friedman, Milena Ivanova and Michela Massimi discuss van Fraassen's contributions to philosophy. Three chapters focus on his engagement with realism (French, Friedman, Ivanova). Others study his voluntarism (Cartwright) and his view on representation (Massimi). Finally, there are contributions about his elaboration of empiricism (Dellsén) and his proposal to consider philosophical positions as stances (Egg). The volume includes a laudatio written by Steven French and finishes with a reply by van Fraassen to his critics. (shrink)

What are scientific theories and how should they be represented? In this article, I propose a causal–structural account, according to which scientific theories are to be represented as sets of interrelated causal and credal nets. In contrast with other accounts of scientific theories (such as Sneedian structuralism, Kitcher’s unificationist view, and Darden’s theory of theoretical components), this leaves room for causality to play a substantial role. As a result, an interesting account of explanation is (...) provided, which sheds light on explanatory unification within a causalist framework. The theory of classical genetics is used as a case study. 1 Introduction2 The Theory of Classical Genetics3 Three Philosophical Accounts of the Theory of Classical Genetics3.1 The structuralist account3.2 Kitcher’s unificationism3.3 Darden and theory change in science4 A Common Lacuna: Where is Causality?5 Woodward’s Interventionist Account of Causation6 Causal Bayes Nets and Their Interrelations6.1 Causal Bayes nets6.2 Relations among causal nets6.3 Credal nets and their interrelations7 The Theory of the Gene and its Causal Graph8 A First Exemplar: Stem Length in Pea Plants8.1 Three crosses on stem length in pea plants8.2 The causal graph for stem length in pea plants8.3 Morgan’s explanatory principles and the credal net for stem length in pea plants9 Explaining Mendel’s Crosses: A Causal–Structural Account10 Monohybrid Crosses with Complete Dominance11 Exemplars,Explanatory Patterns, Generic Credal Nets, and Mechanism Schemas12 Incomplete Dominance13 Anomalies14 Multi-hybrid Crosses with Independent Assortment15 Multi-hybrid Crosses with Linkage and Crossing-Over16 Double Crossing-Over and the Linear Order of the Gene17 Causal–Structural Explanation18 Explanatory Unification19 Concluding Remarks. (shrink)

Dawes (2013) claims that we ought not to believe but to accept our best scientific theories. To accept them means to employ them as premises in our reasoning with the goal of attaining knowledge about unobservables. I reply that if we do not believe our best scientific theories, we cannot gain knowledge about unobservables, our opponents might dismiss the predictions derived from them, and we cannot use them to explain phenomena. We commit an unethical speech act (...) when we explain a phenomenon in terms of a theory we do not believe. (shrink)

The paper deals with the transformation of plant breeding from an agricultural practice into an applied academic science in the late 19th and early 20th centuries Germany. The aim is to contribute to the ongoing debate about the relationship between science and technology. After a brief discussion of this debate the first part of the paper examines how pioneers of plant breeding developed their breeding methods and commercially successful varieties. The focus here is on the role of scientific concepts (...) and theories in the agricultural innovation process. The second part turns towards the strategies by which agronomists tried to establish plant breeding as an academic discipline and themselves as the new experts for breeding research and varietal development. Again, the focus is on the interplay of scientific theory and agricultural practice. It is argued that in order to better understand the transformation of plant breeding into an applied academic science we have to take different levels into account, i.e. the levels of organizations, individuals and objects, at which science and technology interact. (shrink)

A close examination of the literature on ontology may strike one with roughly two distinct senses of this word. According to the first of them, which we shall call traditional ontology , ontology is characterized as the a priori study of various “ontological categories”. In a second sense, which may be called naturalized ontology , ontology relies on our best scientific theories and from them it tries to derive the ultimate furniture of the world. From a methodological point (...) of view these two senses of ontology are very far away. Here, we discuss a possible relationship between these senses and argue that they may be made compatible and complement each other. We also examine how logic, understood as a linguistic device dealing with the conceptual framework of a theory and its basic inference patterns must be taken into account in this kind of study. The idea guiding our proposal may be put as follows: naturalized ontology checks for the applicability of the ontological categories proposed by traditional ontology and give substantial feedback for it. The adequate expression of some of the resulting ontological frameworks may require a different logic. We conclude with a discussion of the case of orthodox quantum mechanics, arguing that this theory exemplifies the kind of relationship between the two senses of ontology. We also argue that the view proposed here may throw some light in ontological questions concerning this theory. (shrink)

Hierarchical Bayesian models (HBMs) provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘paradigms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher‐level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly (...) the idea that higher‐level theories guide learning at lower levels. In addition, they help resolve certain issues for Bayesians, such as scientific preference for simplicity and the problem of new theories. *Received July 2009; revised October 2009. †To contact the authors, please write to: Leah Henderson, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 32D‐808, Cambridge, MA 02139; e‐mail: [email protected]. (shrink)