The mathematical theory of communication.

Described by the philosopher A.J. Ayer as a work of 'great originality and power', this book revolutionized contemporary thinking on science and knowledge. Ideas such as the now legendary doctrine of 'falsificationism' electrified the scientific community, influencing even working scientists, as well as post-war philosophy. This astonishing work ranks alongside The Open Society and Its Enemies as one of Popper's most enduring books and contains insights and arguments that demand to be read to this day.

Essentialism is the idea that certain categories, such as "dog," "man," or "intelligence," have an underlying reality or true nature that gives objects their identity. Where does this idea come from? In this book, Susan Gelman argues that essentialism is an early cognitive bias. Young children's concepts reflect a deep commitment to essentialism, and this commitment leads children to look beyond the obvious in many converging ways: when learning words, generalizing knowledge to new category members, reasoning about the insides of (...) things, contemplating the role of nature versus nurture, and constructing causal explanations. Gelman argues against the standard view of children as concrete or focused on the obvious, instead claiming that children have an early, powerful tendency to search for hidden, non-obvious features of things. She also attacks claims that children build up their knowledge of the world based on simple, associative learning strategies, arguing that children's concepts are embedded in rich folk theories. Parents don't explicitly teach children to essentialize; instead, during the preschool years, children spontaneously construct concepts and beliefs that reflect an essentialist bias.Essentialist accounts have been offered, in one form or another, for thousands of years, extending back at least to Aristotle and Plato. Yet this book is the first to address the issues surrounding essentialism from a psychological perspective. Gelman synthesizes over 15 years of empirical research on essentialism into a unified framework and explores the broader lessons that the research imparts concerning, among other things, human concepts, children's thinking, and the ways in which language influences thought. This volume will appeal to developmental, cognitive, and social psychologists, as well as to scholars in cognitive science and philosophy. (shrink)

Shepard has argued that a universal law should govern generalization across different domains of perception and cognition, as well as across organisms from different species or even different planets. Starting with some basic assumptions about natural kinds, he derived an exponential decay function as the form of the universal generalization gradient, which accords strikingly well with a wide range of empirical data. However, his original formulation applied only to the ideal case of generalization from a single encountered stimulus to a (...) single novel stimulus, and for stimuli that can be represented as points in a continuous metric psychological space. Here we recast Shepard's theory in a more general Bayesian framework and show how this naturally extends his approach to the more realistic situation of generalizing from multiple consequential stimuli with arbitrary representational structure. Our framework also subsumes a version of Tversky's set-theoretic model of similarity, which is conventionally thought of as the primary alternative to Shepard's continuous metric space model of similarity and generalization. This unification allows us not only to draw deep parallels between the set-theoretic and spatial approaches, but also to significantly advance the explanatory power of set-theoretic models. Key Words: additive clustering; Bayesian inference; categorization; concept learning; contrast model; features; generalization; psychological space; similarity. (shrink)