Concept learning and flexible weighting

Aha, D. W., and Goldstone, R. L. (1992). Concept learning and flexible weighting. Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society. (pp. 534-539). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

We previously introduced an exemplar model, named GCM-ISW, that exploits a highly flexible weighting scheme. Or simulations showed that it records faster learning rates and higher asymptotic accuracies on several artificial categorization tasks than models with more limited abilities to warp input spaces. This paper extends our previous work; it describes experimental results that suggest human subjects also invoke such highly flexible schemes. In particular, our model provides significantly better fits than models with less flexibility, and we hypothesize that humans selectively weight attributes depending on an item`s location in the input space.

Feature diagnosticity as a tool for investigating positively and negatively defined concepts

Goldstone, R. L. (1991). Feature diagnosticity as a tool for investigating positively and negatively defined concepts. Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society. (pp. 263-268). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

Two methods of representing concepts are distinguished and empirically investigated. Negatively defined concepts are defined in terms of other concepts at the same level of abstraction. Positively defined concepts do not make recourse to other concepts at the same level of abstraction for their definition. In two experiments, subjects are biased to represent concepts underlying visual patterns in a positive manner by instructing subjects to form an image of the learned concepts and by initially training subjects on minimally distorted concept instances. Positively defined concepts are characterized by a large use of non-diagnostic features in concept representations, relative to negatively defined concepts. The distinction between positively and negatively defined concepts can account for the dual nature of natural concepts – as directly accessed during the recognition of items, and is intricately interconnected to other concepts.

Relational similarity and the nonindependence of features in similarity judgments

Goldstone, R. L., Medin, D. L., & Gentner, D. (1991). Relational similarity and the nonindependence of features in similarity judgments. Cognitive Psychology, 23, 222-264

Four experiments examined the hypothesis that simple attributional features and relational features operate differently in the determination of similarity judgements. Forced choice similarity judgments (“Is X or Y more similar to Z?”) and similarity rating tasks demonstrate that making the same featural change in two geometric stimuli unequally affects their judged similarity to a third stimulus (the comparison stimulus). More specifically, a featural change that causes stimuli to be more superficially similar and less relationally similar increases judged similarity if it occurs in stimuli that already share many superficial attributes, and decreases similarity if it occurs in stimuli that do not share as many superficial attributes. These results argue against an assumption of feature independence which asserts that the degree to which a feature shared by two objects affects similarity is independent of the other features shared by the objects. The MAX hypothesis is introduced, in which attributional and relational similarities are separately pooled, and shared features affect similarity more if the pool they are in is already relatively large. The results support claims that relations and attributes are psychologically distinct and that formal measures of similarity should not treat all types of matching features equally.

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Learning attribute relevance in context in instance-based learning algorithms

Aha, D. W., and Goldstone, R. L. (1990). Learning attribute relevance in context in instance-based learning algorithms. Proceedings of the Twelfth Annual Conference of the Cognitive Science Society. (pp. 141-148). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

There has been an upsurge of interest, in both artificial intelligence and cognitive psychology, in exemplar-based process models of categorization, which preserve specific instances instead of maintaining abstractions derived from them. Recent exemplar-based models provided accurate fits for subject results in a variety of experiments because, in accordance with Shepard`s (1987) observations, they define similarity to degrade exponentially with the distance between instances in psychological space. Although several researchers have shown that an attribute`s relevance in similarity calculations varies according to its context (i.e., the values of the other attributes in the instance and the target concept,” previous exemplar models define attribute relevance to be invariant across all instances. This paper introduces the GCM-ISW model, an extension of Nosofsky`s GCM model that uses context-specific attribute weights for categorization tasks. Since several researchers have reported that humans make context-sensitive classification decision, our model will fit subject data more accurately when attribute relevance is context-sensitive. We also introduce a process component for GCM-ISW and show that its learning rate is significantly faster than the rates of both previous exemplar-based process models when attribute relevance varies among instances. GCM-ISM is both computationally more efficient and more psychologically plausible than previous exemplar-based models.

Similarity involving attributes and relations: Judgments of similarity and difference are not inverses

Medin, D. L., Goldstone, R. L., & Gentner, D. (1990). Similarity involving attributes and relations: Judgments of similarity and difference are not inverses. Psychological Science, 1, 64-69.

Conventional wisdom and previous research suggest that similarity judgements and difference judgements are inverses of one another. An exception to this rule arises when both relational similarity and attributional similarity are considered. When presented with choices that are relationally or attributionally similar to a standard, human subjects tend to pick the relationally similar choice as more similar to the standard and as more different from the standard. These results not only reinforce the general distinction between attributes and relations but also show that attributes and relations are dynamically distinct in the processes that give rise to similarity and difference judgments.

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