Strategic differences in spatial tasks can be explained in terms of different cognitive coordinate systems that subjects adopt. The strategy of mental rotation that occurs in many recent experiments uses a coordinate system denned by the standard axes of our visual world (i. e., horizontal, vertical, and depth axes). Several other possible coordinate systems (and hence other strategies) for solving the problems that occur in psychometric tests of spatial ability are examined in this article. One alternative strategy uses a coordinate system denned by the demands of each test item, resulting in mental rotation around arbitrary, taskdefined axes. Another strategy uses a coordinate system denned exclusively by the objects, producing representations that are invariant with the objects ' orientation. A detailed theoretical account of the mental rotation of individuals of low and high spatial ability, solving problems taken from psychometric tests, is instantiated as two related computer simulation models whose performance corresponds to the response latencies, eye-fixation patterns, and retrospective strategy reports of the two ability groups. The main purpose of this article is to provide a theory of how people solve problems on psychometric tests of spatial ability, focusing on the mental operations, representations, and strategies that are used for different types of problems. The theory is instantiated in terms of computer simulation models whose performance characteristics resemble human characteristics. A second purpose of the article is to analyze the processing differences between people of high and low spatial ability. One computer model simulates the processes

Route directions are usually conveyed either by graphical means, i.e.

A new cognitive architecture for artificial vision is proposed. The architecture, aimed at an autonomous intelligent system, is cognitive in the sense that several cognitive hypotheses have been postulated as guidelines for its design. The first one is the existence of a conceptual representation level between the subsymbolic level, that processes sensory data, and the linguistic level, that describes scenes by means of a high-level language. The conceptual level plays the role of the interpretation domain for the symbols at the linguistic levels. A second cognitive hypothesis concerns the active role of a focus of attention mechanism in the link between the conceptual and the linguistic level: the exploration process of the perceived scene is driven by linguistic and associative expectations. This link is modeled as a timedelay attractor neural network. Results are reported obtained by an experimental implementation of the architecture.

Reverse engineering is the process of extracting system abstractions and design information out of existing software systems. This information can then be used for subsequent development, maintenance, re-engineering, or reuse purposes. This process involves the identification of software artifacts in a particular subject system, and the aggregation of these artifacts to form more abstract system representations. This paper describes a reverse engineering environment which uses the spatial and visual information inherent in graphical representations of software systems to form the basis of a software interconnection model. This information is displayed and manipulated by the reverse engineer using an interactive graph editor to build subsystem structures out of software building blocks. The spatial component constitutes information about the relative positions of the meaningful parts of a software structure, whereas the visual component contains information about how a software structu...

Qualitative spatial reasoning has seen little progress This paper attempts to explain why We provide a framework for qualitative kinematics (QK), qualitative spatial reasoning about motion We propose that no general-purpose, purely qualitative kinematics exists. We propose instead the MD/PV model of spatial reasoning, which combines the power of diagrams with qualitative representations Next we propose connectivity as the organizing principle for kinematic state, and describe a set of basic inferences which every QK system must make. The framework's utility is illustrated by considering two programs, one finished and one in progress We end by discussing the research questions this framework raises. I.

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor --- a sequence of steps --- with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think.

INTRODUCTION Young disciplines often experience moments of doubt: "Are we doing the right thing?" or "Is this approach viable?" [1]. Nowhere is this better exemplified than in the study of computer vision [2]. While progress has been made, the goal of general vision, on the order of human visual perception, remains elusive. Recently, this has led * Please address all correspondence to Michael J. Tarr, P.O. Box 208205, New Haven, CT 06520-8205, E-mail address: tarr@cs.yale.edu to the suggestion that the entire endeavor is flawed, that we should discard the dominant paradigm, and that it should be replaced with a new, more practical alternative. While this position may not qualify as a "paradigm shift" [3], it certainly advocates a substantial change in direction. To justify this radical deviation, proponents of the new, so-called purposive approach muster three lines of support: first, that machines fall far short of the visual capabilities of humans; second, that current com

The ability to combine words into novel sentences has been used to argue that humans have symbolic language production abilities. Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998). To address these issues, a connectionist model of sentence production was developed. The model had variables (role-concept bindings) that were inspired by spatial representations (Landau & Jackendoff, 1993). In order to take advantage of these variables, a novel dual-pathway architecture with event semantics is proposed and shown to be better at symbolic generalization than several variants. This architecture has one pathway for mapping message content to words and a separate pathway that enforces sequencing constraints. Analysis of the model’s hidden units demonstrated that the model learned different types of information in each pathway, and that the model’s compositional behavior arose from the combination of these two pathways. The model’s ability to balance symbolic and statistical behavior in syntax acquisition and to model aphasic double dissociations provided independent support for the dual-pathway architecture.

Findings in the social psychology literatures on attitudes, social perception, and emotion demonstrate that social information processing involves embodiment, where embodiment refers both to actual bodily states and to simulations of experience in the brain’s modality-specific systems for perception, action, and introspection. We show that embodiment underlies social information processing when the perceiver interacts with actual social objects (online cognition) and when the perceiver represents social objects in their absence (offline cognition). Although many empirical demonstrations of social embodiment exist, no particularly compelling account of them has been offered. We propose that theories of embodied cognition, such as the Perceptual Symbol Systems (PSS) account (Barsalou, 1999), explain and integrate these findings, and that they also suggest exciting new directions for research. We compare the PSS account to a variety of related proposals and show how it addresses criticisms that have previously posed problems for the general embodiment approach. Consider the following findings. Wells and Petty (1980) reported that nodding the head (as in agreement)

Abstract. The rapidly developing field of diagrammatic knowledge representation and reasoning is surveyed. The origins and rationale of the field, basic principles and methodologies, as well as selected applications are discussed. Closely related areas, like visual languages, data presentation, and visualization are briefly introduced as well. Basic sources of material for further study are indicated. Key words: diagrammatic representation, diagrammatic reasoning, visual languages, diagrams, visual programming, data presentation, visualization, knowledge representation, computer graphics, qualitative physics, geometry theorem proving. 1.