This paper provides a concise overview of Constructions at Work (Goldberg 2006). The book aims to investigate the relevant levels of generalization in adult language, how and why generalizations are learned by children, and how to account for cross-linguistic generalizations.

The authors find East Asians to be holistic, attending to the entire field and assigning causality to it, making relatively little use of categories and formal logic, and relying on "dialectical" reasoning, whereas Westerners, are more analytic, paying attention primarily to the object and the categories to which it belongs and using rules, including formal logic, to understand its behavior. The 2 types of cognitive processes are embedded in different naive metaphysical systems and tacit epistemologies. The authors speculate that the (...) origin of these differences is traceable to markedly different social systems. The theory and the evidence presented call into question long-held assumptions about basic cognitive processes and even about the appropriateness of the process–content distinction. (shrink)

In contrast to earlier views that argued for a particular kind of concept, several recent accounts have proposed that there are multiple distinct kinds of concepts, or that there is a plurality of concepts for each category. In this paper, I argue for a novel account of concepts as pluralistic hybrids. According to this view, concepts are pluralistic because there are several concepts for the same category whose use is heavily determined by context. In addition, concepts are hybrids because they (...) typically link together several different kinds of information that are used in the same cognitive processes. This alternative view accounts for the available empirical data, allows for greater cognitive flexibility than Machery's recent account, and overcomes several objections to traditional hybrid views. (shrink)

Similarity underlies fundamental cognitive capabilities such as memory, categorization, decision making, problem solving, and reasoning. Although recent approaches to similarity appreciate the structure of mental representations, they differ in the processes posited to operate over these representations. We present an experiment that differentiates among extant structural accounts of similarity in their ability to account for patterns of similarity ratings. These data pose a challenge for transformation‐based models and all but one mapping‐based model, the Similarity as Interactive Activation and Mapping (SIAM) (...) model of similarity. (shrink)

Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases—assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed data. This article explores a novel experimental method for identifying the biases that guide human inductive inferences. The idea behind this method is simple: This article uses the responses (...) produced by a participant on one trial to generate the stimuli that either they or another participant will see on the next. A formal analysis of this “iterated learning” procedure, based on the assumption that the learners are Bayesian agents, predicts that it should reveal the inductive biases of these learners, as expressed in a prior probability distribution over hypotheses. This article presents a series of experiments using stimuli based on a well-studied set of category structures, demonstrating that iterated learning can be used to reveal the inductive biases of human learners. (shrink)

Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key ‘‘sampling’’ assumption about how the available data were generated. Previous models have considered two extreme possibilities, known as strong and weak sampling. In strong sampling, data are assumed to have been deliberately generated as positive examples of a concept, whereas in weak sampling, (...) data are assumed to have been generated without any restrictions. We develop a more general account of sampling that allows for an intermediate mixture of these two extremes, and we test its usefulness. In two experiments, we show that most people complete simple one-dimensional generalization tasks in a way that is consistent with their believing in some mixture of strong and weak sampling, but that there are large individual differences in the relative emphasis different people give to each type of sampling. We also show experimentally that the relative emphasis of the mixture is influenced by the structure of the available information. We discuss the psychological meaning of mixing strong and weak sampling, and possible extensions of our modeling approach to richer problems of inductive generalization. (shrink)

The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt of providing a satisfactory account of the phenomenon has proven challenging. Here, we elaborate the suggestion (first discussed by Sides et al., 2001) that in standard conjunction problems the fallacious probability judgments experimentally observed are typically guided by sound assessments of confirmation relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal result is (...) a confirmation-theoretic account of the conjuntion fallacy which is proven robust (i.e., not depending on various alternative ways of measuring degrees of confirmation). The proposed analysis is shown distinct from contentions that the conjunction effect is in fact not a fallacy and is compared with major competing explanations of the phenomenon, including earlier references to a confirmation-theoretic account. (shrink)

We provide a 'verisimilitudinarian' analysis of the well-known Linda paradox or conjunction fallacy, i.e., the fact that most people judge the probability of the conjunctive statement "Linda is a bank teller and is active in the feminist movement" (B & F) as more probable than the isolated statement "Linda is a bank teller" (B), contrary to an uncontroversial principle of probability theory. The basic idea is that experimental participants may judge B & F a better hypothesis about Linda as compared (...) to B because they evaluate B & F as more verisimilar than B. In fact, the hypothesis "feminist bank teller", while less likely to be true than "bank teller", may well be a better approximation to the truth about Linda. (shrink)

Although cognitive scientists have learned a lot about concepts, their findings have yet to be organized in a coherent theoretical framework. In addition, after twenty years of controversy, there is little sign that philosophers and psychologists are converging toward an agreement about the very nature of concepts. Doing without Concepts (Machery 2009) attempts to remedy this state of affairs. In this article, I review the main points and arguments developed at greater length in Doing without Concepts.

This essay addresses the methodology of philosophy of science and illustrates how formal and empirical methods can be fruitfully combined. Special emphasis is given to the application of experimental methods to confirmation theory and to recent work on the conjunction fallacy, a key topic in the rationality debate arising from research in cognitive psychology. Several other issue can be studied in this way. In the concluding section, a brief outline is provided of three further examples.

In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...) (5) how concepts reorganize between the ages of 4 and 10, and (6) the relationship between causal knowledge and semantic knowledge. The explanations our theory offers for these phenomena are illustrated with reference to a simple feed-forward connectionist model. The relationships between this simple model, the broader theory, and more general issues in cognitive science are discussed. (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)

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...) described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity. Key Words: categorization; cognitive explanation; language; learning; reasoning; rules; similarity. (shrink)

There is a general conception of levels in philosophy which says that the world is arrayed into a hierarchy of levels and that there are different modes of analysis that correspond to each level of this hierarchy, what can be labelled the ‘Hierarchical Correspondence View of Levels” (or HCL). The trouble is that despite its considerable lineage and general status in philosophy of science and metaphysics the HCL has largely escaped analysis in specific domains of inquiry. The goal of this (...) paper is to take up a recent call to domain-specificity by examining the role of the HCL in cognitive science. I argue that the HCL is, in fact, a conception of levels that has been employed in cognitive science and that cognitive scientists should avoid its use where possible. The argument is that the HCL is problematic when applied to cognitive science specifically because it fails to distinguish two important kinds of shifts used when analysing information processing systems: shifts in grain and shifts in analysis. I conclude by proposing a revised version of the HCL which accommodates the distinction. (shrink)

Categorization behavior can be fruitfully analyzed in terms of the trade‐off between as high as possible faithfulness in the transmission of information about samples of the classes to be categorized, and as low as possible transmission costs for that same information. The kinds of categorization behaviors we associate with conceptual atoms, prototypes, and exemplars emerge naturally as a result of this trade‐off, in the presence of certain natural constraints on the probabilistic distribution of samples, and the ways in which we (...) measure faithfulness. Beyond the general structure of categorization in these circumstances, the same information‐centered perspective can shed light on other, more concrete properties of human categorization performance, such as the results of certain prominent experiments on supervised categorization. (shrink)

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from (...) conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. (shrink)

Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory which are typically based on similarity or rule functions as explanations of how categories emerge. Although these theories work well at modeling highly controlled stimuli in laboratory settings, they often perform less well outside of these settings, such as explaining (...) the emergence of background knowledge processes. In order to explain background knowledge, we present a non-similarity-based post-Skinnerian theory of human language called Relational Frame Theory (RFT) which is rooted in a philosophical world view called functional contextualism (FC). This theory offers a very different interpretation of how categories emerge through the functions of behavior and through contextual cues, which may be of some benefit to existing categorization theories. Specifically, RFT may be able to offer a novel explanation of how background knowledge arises, and we provide some mathematical considerations in order to identify a formal model. Finally, we discuss much of this work within the broader context of general semantic knowledge and artificial intelligence research. (shrink)

This paper reports the first empirical investigation of the hypothesis that epistemic appraisals form part of the structure of concepts. To date, studies of concepts have focused on the way concepts encode properties of objects and the way those features are used in categorization and in other cognitive tasks. Philosophical considerations show the importance of also considering how a thinker assesses the epistemic value of beliefs and other cognitive resources and, in particular, concepts. We demonstrate that there are multiple, reliably (...) judged, dimensions of epistemic appraisal of concepts. Four of these dimensions are accounted for by a common underlying factor capturing how well people believe they understand a concept. Further studies show how dimensions of concept appraisal relate to other aspects of concepts. First, they relate directly to the hierarchical organization of concepts, reflecting the increase in specificity from superordinate to basic and subordinate levels. Second, they predict inductive choices in category-based induction. Our results suggest that epistemic appraisals of concepts form a psychologically important yet previously overlooked aspect of the structure of concepts. These findings will be important in understanding why individuals sometimes abandon and replace certain concepts; why social groups do so, for example, during a “scientific revolution”; and how we can facilitate such changes when we engage in deliberate “conceptual engineering” for epistemic, social, and political purposes. (shrink)

Category-based induction is an inferential mechanism that uses knowledge of conceptual relations in order to estimate how likely is for a property to be projected from one category to another. During the last decades, psychologists have identified several features of this mechanism, and they have proposed different formal models of it. In this article; we propose a new mathematical model for category-based induction based on distances on conceptual spaces. We show how this model can predict most of the properties of (...) this kind of reasoning while providing a solid theoretical foundation for it. We also show that it subsumes some of the previous models proposed in the literature and that it generates new predictions. (shrink)

Recent work in folk metaethics finds a correlation between perceived consensus about a moral claim and meta-ethical judgments about whether the claim is universally or only relatively true. We argue that consensus can provide evidence for meta-normative claims, such as whether a claim is universally true. We then report several experiments indicating that people use consensus to make inferences about whether a claim is universally true. This suggests that people's beliefs about relativism and universalism are partly guided by evidence-based reasoning. (...) In a final study, we show that the rejection of universalism does not generate a simple subjectivism but is associated with a more moderate relativism on which highly atypical positions are regarded as mistaken. (shrink)

The remarkable transition from helpless infant to sophisticatedfive-year-old has long captured the attention of scholars interested inthe discovery of knowledge. To explain these achievements, developmentalpsychologists often compare children's discovery procedures to those ofprofessional scientists. For the child to be qualified as a ``littlescientist'', however, intellectual development must be shown to derivefrom rational hypothesis selection in the face of evidence. In thepresent paper we focus on one dimension of rational theory-choice,namely, the relation between hypothesis confirmation and evidencediversity. Psychological research suggests cultural (...) variability inappreciating evidence diversity and lack of such appreciation by youngchildren. Before reaching conclusions about the ``little scientist''thesis, however, it is essential to normatively analyze the diversityissue. We undertake such an analysis within a Bayesianperspective. (shrink)

Researchers have debated whether there is a relationship between a statement’s truth-value and whether it counts as a lie. One view is that a statement being objectively false is essential to whether it counts as a lie; the opposing view is that a statement’s objective truth-value is inessential to whether it counts as a lie. We report five behavioral experiments that use a novel range of behavioral measures to address this issue. In each case, we found evidence of a relationship. (...) A statement’s truth-value affects how quickly people judge whether it is a lie. When people consider the matter carefully and are told that they might need to justify their answer, they are more likely to categorize a statement as a lie when it is false than when it is true. When given options that inhibit perspective-taking, people tend to not categorize deceptively motivated statements as lies when they are true, even though they still categorize them as lies when they are false. Categorizing a speaker as “lying” leads people to strongly infer that the speaker’s statement is false. People are more likely to spontaneously categorize a statement as a lie when it is false than when it is true. We discuss four different interpretations of relevant findings to date. At present, the best supported interpretation might be that the ordinary lying concept is a prototype concept, with falsity being a centrally important element of the prototypical lie. (shrink)

. This paper describes a cross-cultural and developmental research project on naïve or folk biology, that is, the study of how people conceptualize nature. The combination of domain specificity and cross-cultural comparison brings a new perspective to theories of categorization and reasoning and undermines the tendency to focus on “standard populations.” From the standpoint of mainstream cognitive psychology, we find that results gathered from standard populations in industrialized societies often fail to generalize to humanity at large. For example, similarity-driven typicality (...) and diversity effects and basic level phenomena either are not found or pattern differently when we move beyond undergraduates. From the perspective of domain-specificity, standard populations may yield misleading results, because such populations represent examples of especially impoverished experience with respect to nature. Conceptions of humans as biological kinds vary with cultural milieu and input conditions. We also show certain phenomena that are robust across populations, consistent with notions of domain-specificity. (shrink)

Inductive reasoning requires exploiting links between evidence and hypotheses. This can be done focusing either on the posterior probability of the hypothesis when updated on the new evidence or on the impact of the new evidence on the credibility of the hypothesis. But are these two cognitive representations equally reliable? This study investigates this question by comparing probability and impact judgments on the same experimental materials. The results indicate that impact judgments are more consistent in time and more accurate than (...) probability judgments. Impact judgments also predict the direction of errors in probability judgments. These findings suggest that human inductive reasoning relies more on estimating evidential impact than on posterior probability. (shrink)

Studies of categorical induction typically examine how belief in a premise (e.g., Falcons have an ulnar artery) projects on to a conclusion (e.g., Robins have an ulnar artery). We study induction in cases in which the premise is uncertain (e.g., There is an 80% chance that falcons have an ulnar artery). Jeffrey's rule is a normative model for updating beliefs in the face of uncertain evidence. In three studies we tested the descriptive validity of Jeffrey's rule and a related probability (...) theorem, the rule of total probability. Although these rules provided good approximations to mean judgments in some cases, the results from regression and correlation analyses suggest that participants focus on the parts of these rules that are associated with the highest overall probability. We relate our findings to rational models of judgment. (shrink)

The likelihood of a statement is often derived by generating an explanation for it and evaluating the plausibility of the explanation. The explanation discounting principle states that people tend to focus on a single explanation; alternative explanations compete with the effect of reducing one another’s credibility. Two experiments tested the hypothesis that this principle applies to inductive inferences concerning the properties of everyday categories. In both experiments, subjects estimated the probability of a series of statements and the conditional probabilities of (...) those conclusions given other related facts. For example, given that most lawyers make good sales people, what is the probability that most psychologists make good sales people? The results showed that when the fact and the conclusion had the same explanation the fact increased people’s willingness to believe the conclusion, but when they had different explanations the fact decreased the conclusion’s credibility. This decrease is attributed to explanation discounting; the explanation for the fact had the effect of reducing the plausibility of the explanation for the conclusion. (shrink)

Consider the task of predicting which soccer team will win the next World Cup. The bookmakers may judge Brazil to be the team most likely to win, but also judge it most likely that a European rather than a Latin American team will win. This is an example of a non-aligned hierarchy structure: the most probable event at the subordinate level (Brazil wins) appears to be inconsistent with the most probable event at the superordinate level (a European team wins). In (...) this paper we exploit such structures to investigate how people make predictions based on uncertain hierarchical knowledge. We distinguish between aligned and non-aligned environments, and conjecture that people assume alignment. Participants were exposed to a non-aligned training set in which the most probable superordinate category predicted one outcome, whereas the most probable subordinate category predicted a different outcome. In the test phase participants allowed their initial probability judgments about category membership to shift their final ratings of the probability of the outcome, even though all judgments were made on the basis of the same statistical data. In effect people were primed to focus on the most likely path in an inference tree, and neglect alternative paths. These results highlight the importance of the level at which statistical data are represented, and suggest that when faced with hierarchical inference problems people adopt a simplifying heuristic that assumes alignment. (shrink)

We advance a model of human probability judgment and apply it to the design of an extrapolation algorithm. Such an algorithm examines a person's judgment about the likelihood of various statements and is then able to predict the same person's judgments about new statements. The algorithm is tested against judgments produced by thirty undergraduates asked to assign probabilities to statements about mammals.

Generic statements (e.g., “Birds lay eggs”) express generalizations about categories. In this paper, we hypothesized that there is a paradoxical asymmetry at the core of generic meaning, such that these sentences have extremely strong implications but require little evidence to be judged true. Four experiments confirmed the hypothesized asymmetry: Participants interpreted novel generics such as “Lorches have purple feathers” as referring to nearly all lorches, but they judged the same novel generics to be true given a wide range of prevalence (...) levels (e.g., even when only 10% or 30% of lorches had purple feathers). A second hypothesis, also confirmed by the results, was that novel generic sentences about dangerous or distinctive properties would be more acceptable than generic sentences that were similar but did not have these connotations. In addition to clarifying important aspects of generics’ meaning, these findings are applicable to a range of real-world processes such as stereotyping and political discourse. (shrink)

Previous studies with adult participants have investigated reasoning from one or two uncertain premises with simple deductive arguments. Three exploratory experiments were designed to extend these results by investigating the evaluation of the plausibility of the conclusion of "combined" arguments, i.e. arguments constituted by two or more "atomic" standard arguments which each involved the same conclusion and one uncertain premise out of two. One example is "If she meets Nicolas it is very improbable she will go to the swimming pool; (...) if she meets Sophie it is very probable she will go to the swimming pool; she meets Nicolas; she meets Sophie". With two conflicting arguments, one supporting and one unfavourable, participants chose a compromise stance (Exp. 1), unless the thematic content of the premises allows one to consider one argument as more important than the other (Exp. 3). With two favourable arguments and rather unfamiliar materials, two typical behaviours appeared. One consisted in choosing a degree of plausibility of the conclusion that is intermediate between the modals asserted in the premises, and the other in choosing a more favourable degree than the most favourable modal (Exp. 1). The plausibility of the conclusion increased when the number of supporting atomic arguments increased from one to three, and decreased when the number of unfavourable arguments increased (Exp. 2). Theoretical implications are discussed and a model is sketched. (shrink)

“In reality, all arguments from experience are founded on the similarity which we discover among natural objects, and by which we are induced to expect effects similar to those which we have found to follow from such objects. ... From causes which appear similar we expect similar effects.”.

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)

The proposal that the concept of innateness expresses a 'folk biological' theory of the 'inner natures' of organisms was tested by examining the response of biologically naive participants to a series of realistic scenarios concerning the development of birdsong. Our results explain the intuitive appeal of existing philosophical analyses of the innateness concept. They simultaneously explain why these analyses are subject to compelling counterexamples. We argue that this explanation undermines the appeal of these analyses, whether understood as analyses of the (...) vernacular concept or as explications of that concept for the purposes of science. (shrink)

Palatable, unhealthy food stimuli can be devalued via Go/No-Go (GNG) training that consistently pairs such stimuli with motor inhibition. However, it remains unclear whether this devaluation is caused via learned associations with motor inhibition or via inferential learning based on the valence of emitted motor responses. The present research disentangles the effects of motor assignment and response valence in GNG training through task instructions. In two studies, chocolate stimuli were consistently paired with motor inhibition (“no-go”) or with motor excitation (“go”). (...) Task instructions indicated that no-go responses were negatively valenced (“do not take”) and that go responses were positively valenced (“take”), or identified no-go responses as positively valenced (“keep”) and go as negatively valenced (“throw away”). The results show an effect of response valence on chocolate evaluations, but no effect of motor assignment: Chocolate stimuli were consistently devalued following pairings with a negatively valenced response, regardless of whether this response entailed motor inhibition or excitation. These findings align best with an inferential account of GNG training, suggesting that devaluation effects critically depend on inferential processes regarding motor response valence. GNG training procedures may, therefore, be optimised by disambiguating the valence of go and no-go motor responses prior to training. (shrink)