5,168 research outputs found
Conceptual Spaces in Object-Oriented Framework
The aim of this paper is to show that the middle level of
mental representations in a conceptual spaces framework is consistent
with the OOP paradigm. We argue that conceptual spaces framework
together with vague prototype theory of categorization appears to be
the most suitable solution for modeling the cognitive apparatus of
humans, and that the OOP paradigm can be easily and intuitively
reconciled with this framework. First, we show that the prototypebased
OOP approach is consistent with Gärdenfors’ model in terms
of structural coherence. Second, we argue that the product of cloning
process in a prototype-based model is in line with the structure of
categories in Gärdenfors’ proposal. Finally, in order to make the fuzzy
object-oriented model consistent with conceptual space, we
demonstrate how to define membership function in a more cognitive
manner, i.e. in terms of similarity to prototype
Typicality, graded membership, and vagueness
This paper addresses theoretical problems arising from the vagueness of language terms, and intuitions of the vagueness of the concepts to which they refer. It is argued that the central intuitions of prototype theory are sufficient to account for both typicality phenomena and psychological intuitions about degrees of membership in vaguely defined classes. The first section explains the importance of the relation between degrees of membership and typicality (or goodness of example) in conceptual categorization. The second and third section address arguments advanced by Osherson and Smith (1997), and Kamp and Partee (1995), that the two notions of degree of membership and typicality must relate to fundamentally different aspects of conceptual representations. A version of prototype theory—the Threshold Model—is proposed to counter these arguments and three possible solutions to the problems of logical selfcontradiction and tautology for vague categorizations are outlined. In the final section graded membership is related to the social construction of conceptual boundaries maintained through language use
Revealing criterial vagueness in inconsistencies
Sixty undergraduate students made category membership decisions for each of 132
candidate exemplar-category name pairs (e.g., chess – Sports) in each of two separate
sessions. They were frequently inconsistent from one session to the next, both for nominal
categories such as Sports and Fish, and ad hoc categories such as Things You Rescue from
a Burning House. A mixture model analysis revealed that several of these inconsistencies
could be attributed to criterial vagueness: participants adopting different criteria for
membership in the two sessions. This finding indicates that categorization is a probabilistic
process, whereby the conditions for applying a category label are not invariant. Individuals
have various functional meanings of nominal categories at their disposal and entertain
competing goals for ad hoc categories
Delving deeper into color space
So far, color-naming studies have relied on a rather limited set of color stimuli. Most importantly, stimuli have been largely limited to highly saturated colors. Because of this, little is known about how people categorize less saturated colors and, more generally, about the structure of color categories as they extend across all dimensions of color space. This article presents the results from a large Internet-based color-naming study that involved color stimuli ranging across all available chroma levels in Munsell space. These results help answer such questions as how English speakers name a more complex color set, whether English speakers use so-called basic color terms (BCTs) more frequently for more saturated colors, how they use non-BCTs in comparison with BCTs, whether non-BCTs are highly consensual in less saturated parts of the solid, how deep inside color space basic color categories extend, or how they behave on the chroma dimension
Comparison and contrast in perceptual categorization
People categorized pairs of perceptual stimuli that varied in both category membership and pairwise similarity. Experiments 1 and 2 showed categorization of 1 color of a pair to be reliably contrasted from that of the other. This similarity-based contrast effect occurred only when the context stimulus was relevant for the categorization of the target (Experiment 3). The effect was not simply owing to perceptual color contrast (Experiment 4), and it extended to pictures from common semantic categories (Experiment 5). Results were consistent with a sign-and-magnitude version of N. Stewart and G. D. A. Brown's (2005) similarity-dissimilarity generalized context model, in which categorization is affected by both similarity to and difference from target categories. The data are also modeled with criterion setting theory (M. Treisman & T. C. Williams, 1984), in which the decision criterion is systematically shifted toward the mean of the current stimuli
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The inverse conjunction fallacy
If people believe that some property is true of all members of a class such as sofas, then they should also believe that the same property is true of all members of a conjunctively defined subset of that class such as uncomfortable handmade sofas. A series of experiments demonstrated a failure to observe this constraint, leading to what is termed the inverse conjunction fallacy. Not only did people often express a belief in the more general statement but not in the more specific, but also when they accepted both beliefs, they were inclined to give greater confidence to the more general. It is argued that this effect underlies a number of other demonstrations of fallacious reasoning, particularly in category-based induction. Alternative accounts of the phenomenon are evaluated, and it is concluded that the effect is best interpreted in terms of intensional reasoning [Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment. Psychological Review, 90, 293–315.]
Conceptual centrality and property induction
This thesis examines property generalization among concepts. Its primary objective is to investigate the hypothesis that the more central a feature for a concept, the higher its generalizability to other concepts that share a similar structure (features and dependencies). Its secondary objectives are to examine the relative contributions of feature centrality and feature variability in property induction, whether centrality offers a domain-general or a domain-specific constraint, and whether centrality can operate under conditions of vagueness. Experiments 1 and 2 addressed the centrality hypothesis with centrality measured, whereas Experiments 3 to 14 and 17 with centrality manipulated. Relative feature centrality was manipulated as follows: from a single-dependency chain (Experiments 3 to 7), from the number of properties that depended upon a feature (Experiments 8 to 11 and 17), and from the centrality of the properties that depended upon the critical features (Experiments 12 to 14). The results support the centrality hypothesis. Experiments 12 to 16 addressed the relative contributions of centrality and variability in property induction. Experiments 12 to 14 pitted a central and variable property against a less central and less variable property in judgments of frequency and inductive strength. The results suggest that property induction depends on centrality rather than frequency information, and that centrality can bias the perception of frequency (although the latter results were not clear-cut). Experiments 15 and 16 pitted centrality against variability in information seeking. The results show that centrality information is sought more often than variability information to make an inference, especially amongst dissimilar concepts. Experiments 1 to 16 used animal categories. Experiment 17 examined the centrality hypothesis with artifact categories. The results show centrality effects. Taken together, the Experiments suggest that centrality offers a domain-general constraint. Experiments 5, 8 to 11, and 17 left the properties that depended upon a candidate feature unspecified. A centrality effect was still obtained. The results suggest that centrality can operate under conditions of vagueness. The results are discussed in terms of theories of conceptual structure and models of category-based inference. A model to capture the present findings is also sketched
Against Imperialism in Legal Concepts
The authority of government—and that of its politicians, judges, regulators, and other specific authorities—continues to grow more imperialistic. This is partly due to the imperialism of legal concepts as facilitated by Wittgenstein’s famously non-essentialist treatment of concepts through family resemblance theory. Although non-essentialism or anti-essentialism can be highly valuable in forming religious and literary concepts, and in describing the sometimes incoherent everyday usage of concepts and terms, all legal concepts should be scientific-style essentialist concepts. Such essentialism combats the broad discretion granted and obscured by non-essentialist approaches that allow concepts to absorb contradictory elements and harmfully hold them together, thus allowing legal authorities to choose from among only those elements that suit their purposes in any given case. Instead of arguing for the total exclusion of family resemblance and similar theories from use in legal concepts, I argue for translating non-essentialist concepts into essentialist ones while still using the former’s theory forms. Precise essentialist concepts, with core and non-contradictory properties clearly delineated, are necessary for maximizing the rational and moral legitimacy of law, which coercively regulates the behavior of ordinary citizens at the command of political and legal authorities. Legal rules and commands must be as clear and consistent as reasonably possible not only for optimal rationality and morality, but also for legitimacy in the eyes of those subject to law. This is especially important in an increasingly diverse society of incompatible perspectives and decreasing conscious and unconscious adherence to the Anglo-American legal tradition
Toward a Taxonomy and Computational Models of Abnormalities in Images
The human visual system can spot an abnormal image, and reason about what
makes it strange. This task has not received enough attention in computer
vision. In this paper we study various types of atypicalities in images in a
more comprehensive way than has been done before. We propose a new dataset of
abnormal images showing a wide range of atypicalities. We design human subject
experiments to discover a coarse taxonomy of the reasons for abnormality. Our
experiments reveal three major categories of abnormality: object-centric,
scene-centric, and contextual. Based on this taxonomy, we propose a
comprehensive computational model that can predict all different types of
abnormality in images and outperform prior arts in abnormality recognition.Comment: To appear in the Thirtieth AAAI Conference on Artificial Intelligence
(AAAI 2016
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