Researching Cognitive and Linguistic Aspects of Geographic Space - Las Navas then and now.- Spatial Computing - How spatial structures replace computational effort.- The Cognitive Development of the Spatial Concepts NEXT, NEAR, AWAY and FAR.- From compasses and maps to mountains and territories: Experimental results on geographic cognitive categorization.- Prospects and Challenges of Landmarks in Navigation Services.- Landmarks and a hiking ontology to support wayfinding in a national park during different seasons.- Talking about Place Where It Matters.- Many to Many Mobile Maps.- Cognitive and linguistic ideas in geographic information semantics.- Spatial Relation Predicates In Topographic Feature Semantics.- The Egenhofer-Cohn Hypothesis-or, Topological Relativity?.- Twenty Years of Topological Logic.- Reasoning on Class Relations: an Overview.- Creating perceptually salient animated displays of spatiotemporal coordination in events.- Exploring and Reasoning about Perceptual Spaces for Theatre, New Media Installations and the Performing Arts.

Cognitive and linguistic aspects of geographic space : new perspectives on geographic information research

Cognitive and Linguistic Aspects of Geographic Space: An Introduction.- Section 1: Geographic Space.- 1.1 Geographic Space as a Set of Concrete Geographical Entities.- 1.2 Some Notes on Geographic Information Systems: The Relationship Between their Practical Application and their Theoretical Evolution.- 1.3 A Hand-In-Glove Paradigm for Geography.- Section 2: Cultural Influences on the Conceptualization of Geographic Space.- 2.1 "Through the Door": A View of Space from an Anthropological Perspective.- 2.2 Culture as Input and Output of the Cognitive-Linguistic Processes.- 2.3 Dialogic and Argumentative Structures of Bumper Stickers.- Section 3: Wayfinding and Spatial Cognition.- 3.1 The Development of the Abilities Required to Understand Spatial Representations.- 3.2 Making Sense of Human Wayfinding: Review of Cognitive and Linguistic Knowledge for Personal Navigation with a New Research Directioa.- 3.3 Wayfinding Theory and Research: The Need for a New Approach.- 3.4 The Effect of the Pattern of the Environment on Spatial Knowledge Acquisition.- 3.5 Methods for Measuring Spatial Cognition.- 3.6 Path Finding in Free Space Using Sinusoidal Transforms: III.- Section 4: Cartographic Perspectives.- 4.1 Mapping as Language or Semiotic System: Review and Comment.- 4.2 Plan Information and its Retrieval in Map Interpretation: The View from Semiotics.- 4.3 An Approach to Map/Text Interrelationships.- 4.4 Spatial Knowledge for Image Understanding.- Section 5: Formal Treatment of Space in Mathematics.- 5.1 The Mathematical Modeling of Spatial and Non-Spatial Information in Geographic Information Systems.- 5.2 Map Algebra as a Spatial Language.- 5.3 Qualitative Spatial Reasoning.- 5.4 Relative Representation of Spatial Knowledge: The 2-D Case.- 5.5 Matching Representations of Geographic Locations.- 5.6 The Role of Modal Logics in the Description of a Geographical Information System.- Section 6: User Interfaces and Human-Computer Interaction.- 6.1 A Formalization of Metaphors and Image-Schemas in User Interfaces.- 6.2 Elicitation of Spatial Language to Support Cross-Cultural Geographic Information Systems.- 6.3 UGIX: A Layer Based Model For A GIS User Interface.- 6.4 Deficiencies of SQL as a GIS Query Language.- 6.5 The Role of the User in Generalization within Geographic Information Systems.- 6.6 Virtual Worlds, Inside and Out.- Appendix: NATO Advanced Study Institute Participants.

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Cognitive and linguistic aspects of geographic space

Selecting and arranging parts is the core of a configuration task. The validity of a configuration is defined in terms of constraints. Highly declarative, domain independent and simple to use, the constraint 6atisfaetion problem (CSP) paradigm offers an adequate framework for this task. However, the basic paradigm is not powedul enough to capture or to take advantage of essential aspects of configuration, such as the unknown a priori number of constituent parts of a system or the inherent internal structure of these parts. Although notable effort has been spent on extending the basic paradigm to accommodate these issues, we still lack a comprehensive formalism for configuration. This paper presents the main ideas behind a general constraint-based model of configuration tasks represented as a new class of nonstandard constraint satisfaction problems, called composite CSP. Composite CSP unifies several CSP extensions, providing a more comprehensive and efficient basis for formulating and solving configuration problems.

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Configuration as Composite Constraint Satisfaction

This paper puts forward a general framework for thought about human information processing. It is intended to avoid some of the problems of pipeline or stage models of function. At the same time it avoids the snare of supposing a welter of indefinitely many separate processes. The approach is not particularly original, but rather represents the common elements or presuppositions in a number of modern theories. These presuppositions are not usually explicit, however, and making them so reduces the danger of slipping back into earlier modes of thought.The key point is to distinguish between persisting representations and the processes that translate one representation into another. Various classes or groups of persisting representations can be distinguished by the experimental treatments that interfere with them. In particular, there now seem to be several kinds of short-term or temporary storage, different from each other as well as from longterm memory; the translating processes also have several different modes or kinds. A particularly important aspect of the current position is that a model of this general type no longer requires some external agent to direct and control long sequences of behaviour.

The Maltese cross: A new simplistic model for memory

Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits.After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in high-level vision and motor schemas in the control of dextrous hands.Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans.

Levels of modeling of mechanisms of visually guided behavior

The central issue in artificial intelligence the representation and use of knowledge unifies areas as diverse as natural-language understanding, speech recognition, story understanding, planning, problem solving, and vision. This article focuses on how computational vision systems represent knowledge of the visual world. It examines current methodology under two criteria: descriptive adequacy, the ability of a representational formalism to capture the essential visual properties of objects and the relationships among objects in the visual world, and procedural adequacy, the capability of the representation to support efficient processes of recognition and search. A major theme in computational vision has been the distinction between the methodology of image analysis (or early vision) and scene analysis (or high-level vision). Briefly, image analysis can be characterized as the science of extracting from images useful descriptions of lines, regions, edges, and Ssurface characteristics up to the level of Marr's 21/2 -D sketch. It is generally assumed that image analysis is domain independent and passive, that is, data driven. Scene analysis attempts to recognize visual objects and their configurations. It is viewed as domain dependent and goal driven, mnotivated by the necessity of identifying particular objects expected to be present in a scene. Although some may disagree, these distinctions should be seen not as a strict dichotomy but as a spectrum. Early vision exploits constraint.s that are usually valid in the particular visual world for which it has evolved (or been designed). Although early visioni is predominantly data driven, high-level visual processes must be able to establish parameters for and control the attention of lower level processes. As we argue later, efficient scene analysis systems must combinie goal-driven and datadriven recognition processes. If that dichotomy is actually a spectrum then establishing the exact boundary is not a research issue. In this article, we outline current scene analysis methodology (early vision is ably described elsewherelt2) and identity a number of its deficiencies. In response to these problems, some recent systems use schema-based knowledge representations. Examples taken from one called Mapsee2 illustrate our arguments.

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Havens

Papers

Representing Knowledge of the Visual World