This paper reports the results of a series of experiments designed to establish how non-expert subjects conceptualize geospatial phenomena. Subjects were asked to give examples of geographical categories in response to a series of differently phrased elicitations. The results yield an ontology of geographical categories---a catalogue of the prime geospatial concepts and categories shared in common by human subjects independently of their exposure to scientific geography. When combined with nouns such as feature and object, the adjective geographic elicited almost exclusively elements of the physical environment of geographical scale or size, such as mountain, lake, and river. The phrase things that could be portrayed on a map, on the other hand, produced many geographical scale artefacts (roads, cities, etc.) and flat objects (states, countries, etc.), as well as some physical feature types. These data reveal considerable mismatch as between the meanings assigned to the terms `geography' and `geographic' by scientific geographers and by ordinary subjects, so that scientific geographers are not in fact studying geographical phenomena as such phenomena are conceptualized by nave subjects. The data suggest, rather, a special role in determining the subject-matter of scientific geography for the concept of what can be portrayed on a map. This work has implications for work on usability and interoperability in geographical information science, and it throws light also on subtle and hitherto unexplored ways in which ontological terms such as `object', `entity', and `feature' interact with geographical concepts.

Human concept learning presents a version of the classic problem of induction, which is made particularly difficult by the combination of two requirements: the need to learn from a rich (i.e. nested and overlapping) vocabulary of possible concepts and the need to be able to generalize concepts reasonably from only a few positive examples. I begin this thesis by considering a simple number concept game as a concrete illustration of this ability. On this task, human learners can with reasonable confidence lock in on one out of a billion billion billion logically possible concepts, after seeing only four positive examples of the concept, and can generalize informatively after seeing just a single example. Neither of the two classic approaches to inductive inference -- hypothesis testing in a constrained space of possible rules and computing similarity to the observed examples -- can provide a complete picture of how people generalize concepts in even this simple setting. This thesis prop...

While mereotopology -- the theory of boundaries, contact and separation built up on a mereological foundation -- has found fruitful applications in the realm of qualitative spatial reasoning, it faces problems when its methods are extended to deal with those kinds of spatial and non-spatial reasoning which involve a factor of granularity. This is because granularity cannot easily be represented within a mereology-based framework. We sketch how this problem can be solved by means of a theory of coarse-grained partitions, drawing on methods developed for the manipulation of partitions in the spatial realm and applying these to a range of partitions of non-spatial sorts. We then show how these same methods can be extended to apply to finite sequences of partitions evolving over time, or to what we shall call coarse- and fine-grained histories. Keywords: mereotopology, granularity, ontology, partitions, histories 1. Introduction As a result of a series of important contribut...

Exemplar, prototype, and connectionist models typically assume that events constitute the basic unit of learning and representation in categorization. In these models, each learning event updates a statistical representation of a category independently of other learning events. An implication is that events involving the same individual affect learning independently and are not integrated into a single structure that represents the individual in an internal model of the world. A series of experiments demonstrates that human subjects track individuals across events, establish representations of them, and use these representations in categorization. These findings are consistent with ‘‘representationalism,’ ’ the view that an internal model of the world constitutes a physical level of representation in the brain, and that the brain does not simply capture the statistical properties of events in an undifferentiated dynamical system. Although categorization is an inherently statistical process that produces generalization, pattern completion, frequency effects, and adaptive learning, it is also an inherently representational process that establishes an internal model of the world. As a result, representational structures evolve in memory to track the histories of individuals, accumulate information about them, and simulate

Abstract: A naturalistic scheme of primitive conceptual representations is proposed using the statistical measure of mutual information. It is argued that a concept represents, not the class of objects that caused its tokening, but the class of objects that is most likely to have caused it (had it been tokened), as specified by the statistical measure of mutual information. This solves the problem of misrepresentation which plagues causal accounts, by taking the representation relation to be determined via ordinal relationships between conditional probabilities. The scheme can deal with statistical biases and does not rely on arbitrary criteria. Implications for the theory of meaning and semantic content are addressed. 1.

this paper is to examine how pervasive the effect of memory for a reference set is and how memory is used for naming. Specifically, we investigated how naming an ambiguous object would be affected by recent exposure to common and familiar objects that vary in their similarity to the target object and in their typicality

Abstract: I present an account of mental representation based upon the ‘SINBAD’ theory of the cerebral cortex. If the SINBAD theory is correct, then networks of pyramidal cells in the cerebral cortex are appropriately described as representing, or more specifically, as modelling the world. I propose that SINBAD representation reveals the nature of the kind of mental representation found in human and animal minds, since the cortex is heavily implicated in these kinds of minds. Finally, I show how SINBAD neurosemantics can provide accounts of misrepresentation, equivocal representation, twin cases, and Frege cases. 1.

This essay examines the proposal that psychological essentialism results from a history of natural selection acting on human representation and inference systems. It has been argued that the features that distinguish essentialist representational systems are especially well suited for representing natural kinds. If the evolved function of essentialism is to exploit the rich inductive potential of such kinds, then it must be subserved by cognitive mechanisms that carry out at least three distinct functions: identifying these kinds in the envi - ronment, constructing essentialized representations of them, and constraining inductive infer - ences about kinds. Moreover, there are different kinds of kinds, ranging from nonliving sub - stances to biological taxa to within-species kinds such as sex, and the causal processes that render these categories coherent for the purposes of inductive generalization vary. If the evolved function of essentialism is to support inductive generalization under ignorance of true causes, and if kinds of kinds vary in the implicit assumptions that support valid inductive inferences about them, then we expect different, functionally incompatible modes of essen - tialist thinking for different kinds. In particular, there should be differences in how biological and nonbiological substances, biological taxa, and biological and social role kinds are essen - tialized. The functional differences between these kinds of essentialism are discussed.

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Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.