Online research in philosophy

It is consistent with the evidence in The Origin of Concepts to conjecture that infants' causal representations, like their numerical representations, are not continuous with adults', so that bootstrapping is needed in both cases.

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the representations of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources.

This article proposes an object properties approach to object perception. By thinking about objects as clusters of co-instantiated features that possess certain canonical higher-order object properties we can steer a middle way between two extreme views that are dominant in different areas of empirical research into object perception and the development of the object concept. Object perception should be understood in terms of perceptual sensitivity to those object properties, where that perceptual sensitivity can be explained in a manner consistent with the graded representation approach adopted by some connectionist modellers. The object properties approach does justice to the differences between a perceptual system solving the binding problem, on the one hand, and genuinely perceiving objects, on the other, without running into the theoretical problems associated with treating young infants as 'little scientists'.

Physiological evidence predicts a model of concept categorisation that evolves through direct interaction with object feature selection. The requirement stated by Schyns et al. for feature plasticity is supported, but important caveats raise a question about the level at which feature identification can occur. Visual attribute selection for feature creation is likely to be directed by top-down and attentional processes.

Schyns, Goldstone & Thibaut present reasonable arguments for feature creation in category learning. We argue, however, that they do not provide unequivocal evidence either for the necessity or for the occurrence of feature creation. In an effort to sharpen the debate, we take the stand that a fixed feature approach is to be preferred in the absence of compelling evidence.

Schyns et al. argue that flexibility in categorisation implies “feature creation.” We argue that this notion is flawed, that flexibility can be explained by combinations over fixed feature sets, and that feature creation would in any case fail to explain categorisation. We suggest that flexibility in categorisation is due to pragmatic factors influencing feature combination, rendering feature creation unnecessary.

This paper reports the results of two sets of studies demonstrating 14-month-olds’ tendency to associate an object’s behavior with internal, rather than external features. In Experiment 1 infants were familiarized to two animated cats that each exhibited a different style of self-generated motion. Infants then saw a novel individual that had an internal feature (stomach color) similar to one cat, but an external feature (hat color) similar to the other. Infants looked reliably longer when the individual’s motion was congruent with the hat than when it was congruent with the stomach. Using a converging method involving object choice, Experiment 2 found that infants prioritized the internal feature over the external feature only when the object’s behavior was self-generated. In the absence of self-generated behaviors, however, infants did not show a preference towards the internal feature. Ó 2007 Elsevier B.V. All rights reserved.

Schyns, Goldstone & Thibaut oppose the notion of fixed feature analysis, suggesting the possibility of flexible feature creation in object recognition and categorisation. Such proposals cannot be assessed until clear definitions of the objects in question and their decompositions are formulated. Flexibility may come from the decompositions of objects rather than from feature creation.

The origin of features from nonfeatural information is a problem that should concern all theories of object categorization and recognition, not just the flexible feature approach. In contrast to the idea that new features must originate from combinations of simpler fixed features, we argue that holistic features can be created from a direct imprinting on the visual medium. Furthermore, featural descriptions can emerge from processes that by themselves do not operate on feature detectors. Once acquired, features can be decomposed into component features if required by other categorizations. We therefore argue that it is not necessary to separate holistic and componential approaches to representations, because the latter is a development of the former. The requirements for representational flexibility outstrip the performance of any existing computational models, but specific mechanisms of feature creation are discussed and evaluated. Challenges for feature creation mechanisms are discussed together with the constraints (perceptual, statistical, functional, and task) they will need to satisfy.

Infants were presented with an object that moved into reaching space on a path that was either continuously visible or interrupted by an occluder. Infants’ reaching was reduced sharply when an occluder was present, even though the occluder itself was out of reach and did not serve as a barrier to direct reaching for the object. We account for these findings and for the apparently contrasting findings of experiments using preferential looking methods to assess infants’ object representations, by proposing that (a) object representations increase in precision over the infancy period, and (b) the precision of object representations varies in common ways at all ages as a function of object visibility and task demands.