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

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

Ducks lay eggs' is a true sentence, and `ducks are female' is a false one. Similarly, `mosquitoes carry the West Nile virus' is obviously true, whereas `mosquitoes don't carry the West Nile virus' is patently false. This is so despite the egg-laying ducks' being a subset of the female ones and despite the number of mosquitoes that don't carry the virus being ninety-nine times the number that do. Puzzling facts such as these have made generic sentences defy adequate semantic treatment. (...) However complex the truth conditions of generics appear to be, though, young children grasp generics more quickly and readily than seemingly simpler quantifiers such as `all' and `some'. I present an account of generics that not only illuminates the strange truth conditions of generics, but also explains how young children find them so comparatively easy to acquire. I then argue that generics give voice to our most cognitively primitive generalizations and that this hypothesis accounts for a variety of facts ranging from acquisition patterns to cross-linguistic data concerning the phonological articulation of operators. I go on to develop an account of the nature of these cognitively fundamental generalizations and argue that this account explains the strange truth-conditional behavior of generics. (shrink)

The Rescorla–Wagner model has been a leading theory of animal causal induction for nearly 30 years, and human causal induction for the past 15 years. Recent theories 367) have provided alternative explanations of how people draw causal conclusions from covariational data. However, theoretical attempts to compare the Rescorla–Wagner model with more recent models have been hampered by the fact that the Rescorla–Wagner model is an algorithmic theory, while the more recent theories are all computational. This paper provides a detailed derivation (...) of the long-run behavior of the Rescorla– Wagner model under a wide range of parameters and experimental setups, so that the model can be compared with computational theories. It also shows that the model agrees with competing theories on a wider range of cases than had previously been thought. The paper concludes by showing how recently suggested modifications of the Rescorla–Wagner model impact the long-run behavior of the model. (shrink)

Our knowledge about the world is often expressed by generic sentences, yet their meanings are far from clear. This book provides answers to central problems concerning generics: what do they mean? Which factors affect their interpretation? How can one reason with generics? Cohen proposes that the meanings of generics are probability judgments, and shows how this view accounts for many of their puzzling properties, including lawlikeness. Generics are evaluated with respect to alternatives. Cohen argues that alternatives are induced by the (...) kind as well as by the predicated property, and thus provides a uniform account of the varied interpretations of generics. He studies the formal properties of alternatives and provides a compositional account of their derivation by focus and presupposition. Cohen uses his semantics of generics to provide a formal characterization of adequate default reasoning, and proves some desirable results of this formalism. (shrink)

It is widely agreed that generics tolerate exceptions. It turns out, however, that exceptions are tolerated only so long as they do not violate homogeneity: when the exceptions are not concentrated in a salient “chunk” of the domain of the generic. The criterion for salience of a chunk is cognitive: it is dependent on the way in which the domain is mentally represented. Findings of psychological experiments about the ways in which different domains are represented, and the actors affecting such (...) representations, account for judgments of generic sentences, facts which cannot be explained by linguistics alone. The reason for the homogeneity requirement itself is, in turn, also dependent on cognitive considerations. Generics express default rules, and psychological findings have shown that, the more homogeneous the domain, the easier it is for subjects to infer rules about it. Thus, cognitive results form a crucial part of a comprehensive account of the meaning of a linguistic expression. (shrink)

Cimpian et al. observed that we accept generic statements of the form ‘Gs are f’ on relatively weak evidence, but that if we are unfamiliar with group G and we learn a generic statement about it, we still treat it inferentially in a much stronger way: all Gs are f. This paper makes use of notions like ‘representativeness’, ‘contingency’ and ‘relative difference’ from psychology to provide a uniform semantics of generics that explains why people accept generics based on weak evidence. (...) The spirit of the approach has much in common with Leslie’s cognition-based ideas about generics, but the semantics will be grounded on a strengthening of Cohen’s relative readings of generic sentences. In contrast to Leslie and Cohen, we propose a uniform semantic analysis of generics. The basic intuition is that a generic of the form ‘Gs are f’ is true because f is typical for G, which means that f is valuably associated with G. We will make use of Kahneman and Tversky’s Heuristics and Biases approach, according to which people tend to confuse questions about probability with questions about representativeness, to explain pragmatically why people treat many generic statements inferentially in a much stronger way. (shrink)