Hierarchical Bayesian models 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. (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)

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)

How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural (...) context of the problem; and dynamic processes of reasoning that extend ordinary cognition. Focusing on the third factor, Nersessian draws on cognitive science research and historical accounts of scientific practices to show how scientific and ordinary cognition lie on a continuum, and how problem-solving practices in one illuminate practices in the other. (shrink)

Thomas Kuhn's Structure of Scientific Revolutions became the most widely read book about science in the twentieth century. His terms 'paradigm' and 'scientific revolution' entered everyday speech, but they remain controversial. In the second half of the twentieth century, the new field of cognitive science combined empirical psychology, computer science, and neuroscience. In this book, the theories of concepts developed by cognitive scientists are used to evaluate and extend Kuhn's most influential ideas. Based on case studies of the Copernican revolution, (...) the discovery of nuclear fission, and an elaboration of Kuhn's famous 'ducks and geese' example of concept learning, this volume, first published in 2006, offers accounts of the nature of normal and revolutionary science, the function of anomalies, and the nature of incommensurability. (shrink)