217,877 research outputs found

    Expertise and intuition: A tale of three theories

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    Several authors have hailed intuition as one of the defining features of expertise. In particular, while disagreeing on almost anything that touches on human cognition and artificial intelligence, Hubert Dreyfus and Herbert Simon agreed on this point. However, the highly influential theories of intuition they proposed differed in major ways, especially with respect to the role given to search and as to whether intuition is holistic or analytic. Both theories suffer from empirical weaknesses. In this paper, we show how, with some additions, a recent theory of expert memory (the template theory) offers a coherent and wide-ranging explanation of intuition in expert behaviour. It is shown that the theory accounts for the key features of intuition: it explains the rapid onset of intuition and its perceptual nature, provides mechanisms for learning, incorporates processes showing how perception is linked to action and emotion, and how experts capture the entirety of a situation. In doing so, the new theory addresses the issues problematic for Dreyfus’s and Simon’s theories. Implications for research and practice are discussed

    A connectionist account of the emergence of the literal-metaphorical-anomalous distinction in young children

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    We present the first developmental computational model of metaphor comprehension, which seeks to relate the emergence of a distinction between literal and non-literal similarity in young children to the development of semantic representations. The model gradually learns to distinguish literal from metaphorical semantic juxtapositions as it acquires more knowledge about the vehicle domain. In accordance with Keil (1986), the separation of literal from metaphorical comparisons is found to depend on the maturity of the vehicle concept stored within the network. The model generates a number of explicit novel predictions

    Divorce in cooperatively breeding long-tailed tits: a consequence of inbreeding avoidance?

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    The decision of whether to divorce a breeding partner between reproductive attempts can significantly affect individual fitness. In this paper, we report that 63% of surviving pairs of long-tailed tits Aegithalos caudatus divorced between years. We examine three likely explanations for the high divorce rate in this cooperative breeder. The 'better option' hypothesis predicts that divorce and re-pairing increases an individual's reproductive success. However, divorcees did not secure better partners or more helpers and there was no improvement in their reproductive success following divorce. The 'inbreeding avoidance' hypothesis predicts that females should disperse from their family group to avoid breeding with philopatric sons. The observed pattern of divorce was consistent with this hypothesis because, in contrast to the usual avian pattern, divorce was typical for successful pairs (81%) and less frequent in unsuccessful pairs (36-43%). The 'forced divorce' hypothesis predicts that divorce increases as the number of competitors increases. The pattern of divorce among failed breeders was consistent with this hypothesis, but it fails to explain the overall occurrence of divorce because divorcees rarely re-paired with their partners' closest competitors. We discuss long-tailed tits' unique association between divorce and reproductive success in the context of dispersal strategies for inbreeding avoidance

    RPNet: an End-to-End Network for Relative Camera Pose Estimation

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    This paper addresses the task of relative camera pose estimation from raw image pixels, by means of deep neural networks. The proposed RPNet network takes pairs of images as input and directly infers the relative poses, without the need of camera intrinsic/extrinsic. While state-of-the-art systems based on SIFT + RANSAC, are able to recover the translation vector only up to scale, RPNet is trained to produce the full translation vector, in an end-to-end way. Experimental results on the Cambridge Landmark dataset show very promising results regarding the recovery of the full translation vector. They also show that RPNet produces more accurate and more stable results than traditional approaches, especially for hard images (repetitive textures, textureless images, etc). To the best of our knowledge, RPNet is the first attempt to recover full translation vectors in relative pose estimation

    Cognitive performance in multiple system atrophy

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    The cognitive performance of a group of patients with multiple system atrophy (MSA) of striato-nigral predominance was compared with that of age and IQ matched control subjects, using three tests sensitive to frontal lobe dysfunction and a battery sensitive to memory and learning deficits in Parkinson's disease and dementia of the Alzheimer type. The MSA group showed significant deficits in all three of the tests previously shown to be sensitive to frontal lobe dysfunction. Thus, a significant proportion of patients from the MSA group failed an attentional set-shifting test, specifically at the stage when an extra-dimensional shift was required. They were also impaired in a subject-ordered test of spatial working memory. The MSA group showed deficits mostly confined to measures of speed of thinking, rather than accuracy, on the Tower of London task. These deficits were seen in the absence of consistent impairments in language or visual perception. Moreover, the MSA group showed no significant deficits in tests of spatial and pattern recognition previously shown to be sensitive to patients early in the course of probable Alzheimer's disease and only a few patients exhibited impairment on the Warrington Recognition Memory Test. There were impairments on other tests of visual memory and learning relative to matched controls, but these could not easily be related to fundamental deficits of memory or learning. Thus, on a matching-to-sample task the patients were impaired at simultaneous but not delayed matching to sample, whereas difficulties in a pattern-location learning task were more evident at its initial, easier stages. The MSA group showed no consistent evidence of intellectual deterioration as assessed from their performance on subtests of the Wechsler Adult Intelligence Scale (WAIS) and the National Adult Reading Test (NART). Consideration of individual cases showed that there was some heterogeneity in the pattern of deficits in the MSA group, with one patient showing no impairment, even in the face of considerable physical disability. The results show a distinctive pattern of cognitive deficits, unlike those previously seen using the same tests in patients with Parkinson's and Alzheimer's diseases, and suggesting a prominent frontal-lobe-like component. The implications for concepts of 'subcortical' dementia and 'fronto-striatal' cognitive dysfunction are considered

    What's on your mind? Recent advances in memory detection using the concealed information test

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    Lie detectors can be applied in a wide variety of settings. But this advantage comes with a considerable cost: False positives. The applicability of the Concealed Information Test (CIT) is More limited, yet when it can be applied, the risk of false accusations can be set a priori at a very low level. The CIT assesses the recognition of; critical information that is known only by the examiners and the culprit, for example, the face a an accomplice. Large effects are Obtained with the CIT, whether combined with peripheral, brain, or Motor responses. We see three important challenges for the CIT. First, the false negative rate Of the CIT can be substantial, particularly under :realistic circumstantes. A possible solution Seems to restrict the CIT to highly Salient details. Second, there exist effective faking strategies. Future research will tell whether faking can be detected or even prevented (e.g., Using Overt measures). Third, recognition of critical crime detail's does not necessarily result from criminal activity. It is therefore important to properly embed the CIT in the investigative process, While taking care when drawing conclusions from the test outcome (recognition, not guilt)

    Neural coding strategies and mechanisms of competition

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    A long running debate has concerned the question of whether neural representations are encoded using a distributed or a local coding scheme. In both schemes individual neurons respond to certain specific patterns of pre-synaptic activity. Hence, rather than being dichotomous, both coding schemes are based on the same representational mechanism. We argue that a population of neurons needs to be capable of learning both local and distributed representations, as appropriate to the task, and should be capable of generating both local and distributed codes in response to different stimuli. Many neural network algorithms, which are often employed as models of cognitive processes, fail to meet all these requirements. In contrast, we present a neural network architecture which enables a single algorithm to efficiently learn, and respond using, both types of coding scheme
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