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)

Only human beings have a rich conceptual repertoire with concepts like tort, entropy, Abelian group, mannerism, icon and deconstruction. How have humans constructed these concepts? And once they have been constructed by adults, how do children acquire them? While primarily focusing on the second question, in The Origin of Concepts , Susan Carey shows that the answers to both overlap substantially. Carey begins by characterizing the innate starting point for conceptual development, namely systems of core cognition. Representations of core cognition (...) are the output of dedicated input analyzers, as with perceptual representations, but these core representations differ from perceptual representations in having more abstract contents and richer functional roles. Carey argues that the key to understanding cognitive development lies in recognizing conceptual discontinuities in which new representational systems emerge that have more expressive power than core cognition and are also incommensurate with core cognition and other earlier representational systems. Finally, Carey fleshes out Quinian bootstrapping, a learning mechanism that has been repeatedly sketched in the literature on the history and philosophy of science. She demonstrates that Quinian bootstrapping is a major mechanism in the construction of new representational resources over the course of childrens cognitive development. Carey shows how developmental cognitive science resolves aspects of long-standing philosophical debates about the existence, nature, content, and format of innate knowledge. She also shows that understanding the processes of conceptual development in children illuminates the historical process by which concepts are constructed, and transforms the way we think about philosophical problems about the nature of concepts and the relations between language and thought. (shrink)

Over recent years, the psychology of concepts has been rejuvenated by new work on prototypes, inventive ideas on causal cognition, the development of neo-empiricist theories of concepts, and the inputs of the budding neuropsychology of concepts. But our empirical knowledge about concepts has yet to be organized in a coherent framework. -/- In Doing without Concepts, Edouard Machery argues that the dominant psychological theories of concepts fail to provide such a framework and that drastic conceptual changes are required to make (...) sense of the research on concepts in psychology and neuropsychology. Machery shows that the class of concepts divides into several distinct kinds that have little in common with one another and that for this very reason, it is a mistake to attempt to encompass all known phenomena within a single theory of concepts. In brief, concepts are not a natural kind. Machery concludes that the theoretical notion of concept should be eliminated from the theoretical apparatus of contemporary psychology and should be replaced with theoretical notions that are more appropriate for fulfilling psychologists' goals. The notion of concept has encouraged psychologists to believe that a single theory of concepts could be developed, leading to useless theoretical controversies between the dominant paradigms of concepts. Keeping this notion would slow down, and maybe prevent, the development of a more adequate classification and would overshadow the theoretical and empirical issues that are raised by this more adequate classification. Anyone interested in cognitive science's emerging view of the mind will find Machery's provocative ideas of interest. (shrink)

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

1 Knowledge and Justification This book is an investigation of one central problem which arises in the attempt to give a philosophical account of empirical ...

Philosophers from Hume, Kant, and Wittgenstein to the recent realists and antirealists have sought to answer the question, What are concepts? This book provides a detailed, systematic, and accessible introduction to an original philosophical theory of concepts that Christopher Peacocke has developed in recent years to explain facts about the nature of thought, including its systematic character, its relations to truth and reference, and its normative dimension. Particular concepts are also treated within the general framework: perceptual concepts, logical concepts, and (...) the concept of belief are discussed in detail. The general theory is further applied in answering the question of how the ontology of concepts can be of use in classifying mental states, and in discussing the proper relation between philosophical and psychological theories of concepts. Finally, the theory of concepts is used to motivate a nonverificationist theory of the limits of intelligible thought. Peacocke treats content as broad rather than narrow, and his account is nonreductive and non-Quinean. Yet Peacocke also argues for an interactive relationship between philosophical and psychological theories of concepts, and he plots many connections with work in cognitive psychology. (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 ‘para- digms’ 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. (shrink)

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics (...) as the nature of concepts, hypothesis formation, analogy, and theory justification. (shrink)

In this path-breaking work, Paul Thagard draws on history and philosophy of science, cognitive psychology, and the field of artificial intelligence to develop a ...

A comprehensive introduction to current research on the psychology of concept formation and use.

Judea Pearl has been at the forefront of research in the burgeoning field of causal modeling, and Causality is the culmination of his work over the last dozen or so years. For philosophers of science with a serious interest in causal modeling, Causality is simply mandatory reading. Chapter 2, in particular, addresses many of the issues familiar from works such as Causation, Prediction and Search by Peter Spirtes, Clark Glymour, and Richard Scheines. But philosophers with a more general interest in (...) causation will also profit from reading Pearl’s book, especially the material in chapters 7, 9, and 10, which is self-contained and less technical than other parts of the book. The present review is aimed primarily at readers of the second type. (shrink)

In this important new text, Keith Lehrer introduces students to the major traditional and contemporary accounts of knowing. Beginning with the accepted definition of knowledge as justified true belief, Lehrer explores the truth, belief and justification conditions on the way to a thorough examination of foundation theories of knowledge, externalism and naturalized epistemologies, internalism and modern coherence theories as well as recent reliabilist and causal theories. Lehrer gives all views careful examination and concludes that external factors must be matched by (...) appropriate internal ones to yield knowledge. Readers of Professor Lehrer's earlier book _Knowledge_ will want to know that this text adopts the framework of that classic text. But _Theory of Knowledge_ is a completely rewritten and updated version of that book that has been simplified throughout for student use. (shrink)

This article aims to contribute to the literature on conceptual change by engaging in direct theoretical and empirical comparison of contrasting views. We take up the question of whether naïve physical ideas are coherent or fragmented, building specifically on recent work supporting claims of coherence with respect to the concept of force by Ioannides and Vosniadou [Ioannides, C., & Vosniadou, C. (2002). The changing meanings of force. Cognitive Science Quarterly 2, 5–61]. We first engage in a theoretical inquiry on the (...) nature of coherence and fragmentation, concluding that these terms are not well‐defined, and proposing a set of issues that may be better specified. The issues have to do with contextuality, which concerns the range of contexts in which a concept (meaning, model, theory) applies, and relational structure, which is how elements of a concept (meaning, model, or theory) relate to one another. We further propose an enhanced theoretical and empirical accountability for what and how much one needs to say in order to have specified a concept. Vague specification of the meaning of a concept can lead to many kinds of difficulties.Empirically, we conducted two studies. A study patterned closely on Ioannides and Vosniadou's work (which we call a quasi‐replication) failed to confirm their operationalizations of “coherent.” An extension study, based on a more encompassing specification of the concept of force, showed three kinds of results: (1) Subjects attend to more features than mentioned by Ioannides and Vosniadou, and they changed answers systematically based on these features; (2)We found substantial differences in the way subjects thought about the new contexts we asked about, which undermined claims for homogeneity within even the category of subjects (having one particular meaning associated with “force”) that best survived our quasi‐replication; (3) We found much reasoning of subjects about forces that cannot be accounted for by the meanings specified by Ioannides and Vosniadou. All in all, we argue that, with a greater attention to contextuality and with an appropriately broad specification of the meaning of a concept like force, Ioannides and Vosniadou's claims to have demonstrated coherence seem strongly undermined. Students' ideas are not random and chaotic; but neither are they simply described and strongly systematic. (shrink)

A theory of categorization is presented in which knowledge of causal relationships between category features is represented in terms of asymmetric and probabilistic causal mechanisms. According to causal‐model theory, objects are classified as category members to the extent they are likely to have been generated or produced by those mechanisms. The empirical results confirmed that participants rated exemplars good category members to the extent their features manifested the expectations that causal knowledge induces, such as correlations between feature pairs that are (...) directly connected by causal relationships. These expectations also included sensitivity to higher‐order feature interactions that emerge from the asymmetries inherent in causal relationships. Quantitative fits of causal‐model theory were superior to those obtained with extensions to traditional similarity‐based models that represent causal knowledge either as higher‐order relational features or “prior exemplars” stored in memory. (shrink)