Rules and similarity in adult concept learning

Close, James; Hahn, Ulrike; Hodgetts, Carl J.; Pothos, Emmanuel M.

doi:10.1093/acprof:oso/9780199549221.003.03

Cited by 4 publications

(6 citation statements)

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“…However, identifying an impressionistic painting versus an abstract painting is more difficult, because to a certain extent it relies on the interpretation of the viewer rather than on a strict rule. The distinction between types of categories that have clear rules versus those that do not has been referred to as ill-versus well-defined categories or rule-based versus natural categories (for a review see : Close, Hahn, Hodgetts, & Pothos, 2010). Recent studies have focused on natural (ill-defined) categories as they better resemble the types of categories people commonly use.…”

Section: Category Learningmentioning

confidence: 99%

Metacognitive monitoring during category learning: how success affects future behaviour

Doyle

Hourihan

2015

Memory

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The purpose of the present study was to examine how people's perceptions of their own learning, during a category learning task, matched their performance. In two experiments, participants were asked to learn natural categories, of both high and low variability, and make category learning judgments (CLJs). Variability was manipulated by varying the number of exemplars and the number of times each exemplar was presented within each category. Experiment 1 showed that participants were generally overconfident in their knowledge of low variability families, suggesting that they considered repetition to be more useful for learning than it actually was. CLJs had the largest increase when a trial was correct following an incorrect trial and the largest decrease when an incorrect trial followed a correct trial. Experiment 2 replicated these results, but also demonstrated that global CLJ ratings showed the same bias toward repetition.

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Section: Category Learningmentioning

confidence: 99%

Metacognitive monitoring during category learning: how success affects future behaviour

Doyle

Hourihan

2015

Memory

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“…This associative account of an animal’s classification of similar stimuli (as described by Herrnstein et al [ 22 ]) relies on the associative strength of discriminable features common across a category [ 23 ]. In the absence of verbal communication with their subjects, comparative psychologists have largely limited their inquiries to studies of rule-based concepts [ 24 – 25 ]. While an animal can demonstrate that it has learned the rules imposed by researchers, it hasn’t proved possible to study unsupervised and unrewarded assignment of stimuli into categorical groupings without using language to instruct subjects.…”

Section: Introductionmentioning

confidence: 99%

“…For comparative psychologists, possessing an internal representation that allows an animal to reliably classify stimuli does not immediately indicate that the animal has formed a concept. It is intuitive and well documented that adult humans can flexibly and abstractly manipulate their internal concepts [ 28 ], and can use these concepts to mediate their perceptual categorization [ 24 ]. The majority of studies of adult human cognition rely on language, but without either language or the ability to directly inquire into the nature of an animal’s mental representation, inference is restricted.…”

Section: Introductionmentioning

confidence: 99%

Perceptual category learning of photographic and painterly stimuli in rhesus macaques (Macaca mulatta) and humans

Jensen

Terrace

2017

PLoS ONE

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Humans are highly adept at categorizing visual stimuli, but studies of human categorization are typically validated by verbal reports. This makes it difficult to perform comparative studies of categorization using non-human animals. Interpretation of comparative studies is further complicated by the possibility that animal performance may merely reflect reinforcement learning, whereby discrete features act as discriminative cues for categorization. To assess and compare how humans and monkeys classified visual stimuli, we trained 7 rhesus macaques and 41 human volunteers to respond, in a specific order, to four simultaneously presented stimuli at a time, each belonging to a different perceptual category. These exemplars were drawn at random from large banks of images, such that the stimuli presented changed on every trial. Subjects nevertheless identified and ordered these changing stimuli correctly. Three monkeys learned to order naturalistic photographs; four others, close-up sections of paintings with distinctive styles. Humans learned to order both types of stimuli. All subjects classified stimuli at levels substantially greater than that predicted by chance or by feature-driven learning alone, even when stimuli changed on every trial. However, humans more closely resembled monkeys when classifying the more abstract painting stimuli than the photographic stimuli. This points to a common classification strategy in both species, one that humans can rely on in the absence of linguistic labels for categories.

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“…This associative account of an animal's classification of similar stimuli (as described by Herrnstein et al, 1976) relies on the associative strength of discriminable features common across a category (Lea, 1984). In the absence of verbal communication with their subjects, comparative psychologists have largely limited their inquiries to studies of rule-based concepts (Close et al, 2010;Wright and Lickteig, 2010). While an animal can demonstrate that it has learned the rules imposed by researchers, it hasn't proved possible to study unsupervised and unrewarded assignment of stimuli into categorical groupings without using language to instruct subjects.…”

Section: Introductionmentioning

confidence: 99%

“…For comparative psychologists, possessing an internal representation that allows an animal to reliably classify stimuli does not immediately indicate that the animal has formed a concept. It is intuitive and well documented that adult humans can flexibly and abstractly manipulate their internal concepts (Hampton, 2003), and can use these concepts to mediate their perceptual categorization (Close et al, 2010). The majority of studies of adult human cognition rely on language, but without either language or the ability to directly inquire into the nature of an animal's mental representation, inference is restricted.…”

Section: Introductionmentioning

confidence: 99%

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Humans are highly adept at categorizing visual stimuli, but studies of human categorization are typically validated by verbal reports. This makes it difficult to perform comparative studies of categorization using non-human animals. Interpretation of comparative studies is further complicated by the possibility that animal performance may merely reflect reinforcement learning, whereby discrete features act as discriminative cues for categorization. To assess and compare how humans and monkeys classified visual stimuli, we trained 7 rhesus macaques and 41 human volunteers to respond, in a specific order, to four simultaneously presented stimuli at a time, each belonging to a different perceptual category. These exemplars were drawn at random from large banks of images, such that the stimuli presented changed on every trial. Subjects nevertheless identified and ordered these changing stimuli correctly. Three monkeys learned to order naturalistic photographs; four others, close-up sections of paintings with distinctive styles. Humans learned to order both types of stimuli. All subjects classified stimuli at levels substantially greater than that predicted by chance or by feature-driven learning alone, even when stimuli changed one every trial. However, humans more closely resembled monkeys when classifying the more abstract painting stimuli than the photographic stimuli. This points to a common classification strategy in both species, on which humans can rely on in the absence of linguistic labels for categories.

show abstract

Rules and similarity in adult concept learning

Cited by 4 publications

References 0 publications

Metacognitive monitoring during category learning: how success affects future behaviour

Metacognitive monitoring during category learning: how success affects future behaviour

Perceptual category learning of photographic and painterly stimuli in rhesus macaques (Macaca mulatta) and humans

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