Reasoning with uncertain categories

Five experiments investigated how people use categories to make inductions about objects whose categorisation is uncertain. Normatively, they should consider all the categories the object might be in and use a weighted combination of information from all the categories: bet-hedging. The experiments presented people with simple, artificial categories and asked them to make an induction about a new object that was most likely in one category but possibly in another. The results showed that the majority of people focused on the most likely category in making inductions, although there was a group of consistently normative responders who used information from both categories (about 25% of our college population). Across experiments the overall pattern of results suggests that performance in the task is improved not by understanding the underlying principles of bet-hedging but by increasing the likelihood that multiple categories are in working memory at the time of the induction. We discuss implications for improving everyday inductions.     

Basic objects in natural categories

Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest category cue validity, and are, thus, the most differentiated from one another. The four experiments of Part I define basic objects by demonstrating that in taxonomies of common concrete nouns in English based on class inclusion, basic objects are the most inclusive categories whose members: (a) possess significant numbers of attributes in common, (b) have motor programs which are similar to one another, (c) have similar shapes, and (d) can be identified from averaged shapes of members of the class. The eight experiments of Part II explore implications of the structure of categories. Basic objects are shown to be the most inclusive categories for which a concrete image of the category as a whole can be formed, to be the first categorizations made during perception of the environment, to be the earliest categories sorted and earliest named by children, and to be the categories most codable, most coded, and most necessary in language.     

Chromatic information processing: Rate depends on stimulus location in the category and psychological complexity

Summary Colors are typically categorized, and color sensations can be conceived to lie on a continuum of psychological complexity from simple, sensations provoked by colors that fall near the centers of color categories and that convey predominately a single percept (like blue), to complex, sensations provoked by colors that fall near boundaries between color categories and that convey two percepts (like blue-green). In three experiments we assessed the effect of the location of colors in a category (their psychological complexity) on the rate at which observers identified and classified them. In Experiment 1, observers named category center colors faster than boundary colors. A subsidiary experiment with range-shifted stimuli showed that observers were not merely bisecting a stimulus continuum. In Experiment 2, observers classified a variety of category centers more rapidly than a variety of boundaries. In Experiment 3, observers who first practiced classifying color centers or boundaries as such later classified category centers faster than boundaries. A subsidiary experiment showed that this differential was not selective to particular response category labels. Neither Experiment 2 nor Experiment 3 showed any differential effect of visual field of presentation. The advantage of category center or simple over boundary or complex sensations in chromatic information processing is discussed in terms of the physiological sensitivity of the visual system to color.     

Necessity and natural categories.

Our knowledge of natural categories includes beliefs not only about what is true of them but also about what would be true if the categories had properties other than (or in addition to) their actual ones. Evidence about these beliefs comes from three lines of research: experiments on category-based induction, on hypothetical transformations of category members, and on definitions of kind terms. The 1st part of this article examines results and theories arising from each of these research streams. The 2nd part considers possible unified theories for this domain, including theories based on ideals and norms. It also contrasts 2 broad frameworks for modal category information: one focusing on beliefs about intrinsic or essential properties, the other focusing on interacting causal relations.     

Speeded induction under uncertainty: The influence of multiple categories and feature conjunctions

When people are uncertain about the category membership of an item (e.g., Is it a dog or a dingo?), research shows that they tend to rely only on the dominant or most likely category when making inductions (e.g., How likely is it to befriend me?). An exception has been reported using speeded induction judgments where participants appeared to use information from multiple categories to make inductions (Verde, Murphy, &; Ross, 2005). In two speeded induction studies, we found that participants tended to rely on the frequency with which features co-occurred when making feature predictions, independently of category membership. This pattern held whether categories were considered implicitly (Experiment 1) or explicitly (Experiment 2) prior to feature induction. The results converge with other recent work suggesting that people often rely on feature conjunction information, rather than category boundaries, when making inductions under uncertainty.     

What children infer from social categories

Children hold the belief that social categories have essences. We investigated what kinds of properties children feel licensed to infer about a person based on social category membership. Seventy-two 4-6-year-olds were introduced to novel social categories defined as having one internal - psychological or biological - and one external - behavioral or physical - property. For half of the participants, the internal property was described as causing the external one; for the others, no causal relationship between properties was mentioned. Children were asked to choose as a novel exemplar of a category one with only the internal or only the external property. Children inferred that exemplars had a psychological property irrespective of causal status, but they inferred the presence of a biological property only when described as causal. Children did not draw systematic inferences regarding either of the two external properties. These findings indicate that children treat psychological and causal properties as central - and perhaps essential - to human kinds.     

Knowledge-based classification of ill-defined categories

In this paper, I report an exploratory study which investigated the role that prior knowledge plays in influencing classification learning. Under neutral or knowledge-imposing instructions, subjects learned to classify exemplars into categories that either were or were not linearly separable. Linearly separable categories are those categories whose members can be correctly classified based on an additive summation of weighted attribute information. Following category learning, the subjects were given transfer tests. A major finding was that knowledge facilitated the learning of linearly separable categories but interfered with the learning of not linearly separable categories. Quantitative analyses revealed that the knowledge facilitated category learning of the linearly separable categories by influencing the storage and reliance on both prototypical and exemplar information.     

Labels can override perceptual categories in early infancy

An extensive body of research claims that labels facilitate categorisation, highlight the commonalities between objects and act as invitations to form categories for young infants before their first birthday. While this may indeed be a reasonable claim, we argue that it is not justified by the experiments described in the research. We report on a series of experiments that demonstrate that labels can play a causal role in category formation during infancy. Ten-month-old infants were taught to group computer-displayed, novel cartoon drawings into two categories under tightly controlled experimental conditions. Infants were given the opportunity to learn the two categories under four conditions: Without any labels, with two labels that correlated with category membership, with two labels assigned randomly to objects, and with one label assigned to all objects. Category formation was assessed identically in all conditions using a novelty preference procedure conducted in the absence of any labels. The labelling condition had a decisive impact on the way infants formed categories: When two labels correlated with the visual category information, infants learned two categories, just as if there had been no labels presented. However, uncorrelated labels completely disrupted the formation of any categories. Finally, consistent use of a single label across objects led infants to learn one broad category that included all the objects. These findings demonstrate that even before infants start to produce their first words, the labels they hear can override the manner in which they categorise objects.     

On the existence of prelinguistic categories: A case study

The purpose of this study was to investigate whether infants spontaneously form categories during the prelinguistic period and whether these categories are based on the same principles as adult basic-level categories. A new methodology, using a functional use measure as the determinant of category composition, was employed in a case study of one infant's horn category. Results indicated that this category met Schlesinger's (1982) criteria for a prelinguistic category and that the category was based on similarity relationships, as adult categories are.     

Classification versus inference learning contrasted with real-world categories

Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories—what each category is like—while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.     

The flexible use of inductive and geometric spatial categories

The present study examined the flexibility with which people can adopt different category schemes in the spatial domain. In a location memory task, participants viewed and estimated the locations of four kinds of objects that were spatially grouped by object identity. This identity-based arrangement was either congruent or incongruent with the perceptually based, geometric categories that have been reported in previous research. Four experiments examined the conditions under which these different category schemes are used to inform estimates of locations. The results showed that use of identity information depended on the number of objects to be remembered during a trial: When one or two objects were remembered at a time, only geometric categories affected estimates, but when four objects were to be remembered, both geometric categories and identity groupings affected estimates. As memory load increases, participants rely on additional sources to inform their estimates of location.     

Learning categories at different hierarchical levels: a comparison of category learning models

Three formal models of category learning, the rational model (Anderson, 1990), the configural-cue model (Gluck & Bower, 1988a), and ALCOVE (Kruschke, 1992), were evaluated on their ability to account for differential learning of hierarchically structured categories. An experiment using a theoretically challenging category structure developed by Lassaline, Wisniewski, and Medin (1992) is reported. Subjects learned one of two different category structures. For one structure, diagnostic information was present along a single dimension (1-D). For the other structure, diagnostic information was distributed across four dimensions (4-D). Subjects learned these categories at a general or at a specific level of abstraction. For the 1-D structure, specific-level categories were learned more rapidly than general-level categories. For the 4-D structure, the opposite result was observed. These results proved highly diagnostic for evaluating the models—although ALCOVE provided a good account of the observed results, the rational model and the configural-cue model did not.     

Estimating stimuli from contrasting categories: truncation due to boundaries

In this article, the authors present and test a formal model that holds that people use information about category boundaries in estimating inexactly represented stimuli. Boundaries restrict stimuli that are category members to fall within a particular range. This model posits that people increase the average accuracy of stimulus estimates by integrating fine-grain values with boundary information, eliminating extreme responses. The authors present 4 experiments in which people estimated sizes of squares from 2 adjacent or partially overlapping stimulus sets. When stimuli from the 2 sets were paired in presentation, people formed relative size categories, truncating their estimates at the boundaries of these categories. Truncation at the boundary of separation between the categories led to exaggeration of differences between stimuli that cross categories. Yet truncated values are shown to be more accurate on average than unadjusted values.     

Feature inference and the causal structure of categories

The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian networks. In five experiments we found that Bayes' nets generally predicted participants' feature inferences quite well. However, we also observed a pervasive violation of one of the defining principles of Bayes' nets-the causal Markov condition-because the presence of characteristic features invariably led participants to infer yet another characteristic feature. We argue that this effect arises from a domain-general bias to assume the presence of underlying mechanisms associated with the category. Specifically, people take an exemplar to be a "well functioning" category member when it has most or all of the category's characteristic features, and thus are likely to infer a characteristic value on an unobserved dimension.     

Ad hoc categories

People construct ad hoc categories to achieve goals. For example, constructing the category of “things to sell at a garage sale” can be instrumental to achieving the goal of selling unwanted possessions. These categories differ from common categories (e.g., “fruit,” “furniture”) in that ad hoc categories violate the correlational structure of the environment and are not well established in memory. Regarding the latter property, the category concepts, concept-to-instance associations, and instance-to-concept associations structuring ad hoc categories are shown to be much less established in memory than those of common categories. Regardless of these differences, however, ad hoc categories possess graded structures (i.e., typicality gradients) as salient as those structuring common categories. This appears to be the result of a similarity comparison process that imposes graded structure on any category regardless of type.     

Learning time-varying categories

Many kinds of objects and events in our world have a strongly time-dependent quality. However, most theories about concepts and categories either are insensitive to variation over time or treat it as a nuisance factor that produces irrational order effects during learning. In this article, we present two category learning experiments in which we explored peoples’ ability to learn categories whose structure is strongly time-dependent. We suggest that order effects in categorization may in part reflect a sensitivity to changing environments, and that understanding dynamically changing concepts is an important part of developing a full account of human categorization.     

Feature-based versus category-based induction with uncertain categories

Previous research has suggested that when feature inferences have to be made about an instance whose category membership is uncertain, feature-based inductive reasoning is used to the exclusion of category-based induction. These results contrast with the observation that people can and do use category-based induction when category membership is known. The present experiments examined the conditions that drive feature-based and category-based strategies in induction under category uncertainty. Specifically, 2 experiments investigated whether reliance on feature-based inductive strategies is a product of the lack of coherence in the categories used in previous research or is due to the use of a decision-only induction procedure. Experiment 1 found that feature-based reasoning remained the preferred strategy even when categories with relatively high internal coherence were used. Experiment 2 found a shift toward category-based reasoning when participants were trained to classify category members prior to feature induction. Together, these results suggest that an appropriate conceptual representation must be formed through experience with a category before it is likely to be used as a basis for feature induction.     

Failure to find evidence of stimulus generalization within pictorial categories in pigeons

Pigeons' key pecks were reinforced in the presence of pictures from one of two categories, cats or cars. A single picture associated with reinforcement was used in Experiment 1, and 20 pictures from the same category were associated with reinforcement in Experiment 2. Pigeons then were presented with novel test pictures from the training category and from the other, previously unseen, category. During Session 1 of testing, pigeons pecked no more often at pictures from the reinforced category than at pictures from the previously unseen category. When pigeons were trained with pictures associated with reinforcement or its absence from different categories in Experiment 3, differential responding to novel pictures from different categories appeared during Session 1. These findings argue against a process of automatic stimulus generalization within natural categories and in favor of the position that category distinctions are not made until members of at least two categories are compared with one another.