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Sunday, August 2, 2020 | History

3 edition of Cognitive & Computational Models of Spatial Representation found in the catalog.

Cognitive & Computational Models of Spatial Representation

Papers from the 1996 Aaai Spring Symposium (Technical Report)

by Patrick Olivier

  • 79 Want to read
  • 28 Currently reading

Published by AAAI Press .
Written in

    Subjects:
  • General,
  • Science,
  • Science/Mathematics

  • The Physical Object
    FormatPaperback
    Number of Pages109
    ID Numbers
    Open LibraryOL12241184M
    ISBN 101577350057
    ISBN 109781577350057

    models and economic evalqation measures of user benefit. Environment and Planning, A 9: Wilson A G A family of spatial interaction models and associated developments. Environment and Planning, A 3: H. Timmennans Spatial Cognition Spatial . The effects of theta precession on spatial learning and simplicial complex dynamics in a topological model of the hippocampal spatial map. PLoS Comput. Biol. e / [PMC free article] Azizi A. H., Wiskott L., Cheng S. (). A computational model for preplay in the hippocampus. Front. Comput.

    other hand, most current computational cognitive models of spatial memory, which are designed to model biological spatial cognition, cannot deal with all of these challenges, and are thus mostly confined to simplistic simulations (see Madl, Chen, Montaldi, & Trappl () for a review). In addition, although spatial representations in humans. These models are essential for controlling the movement of these body parts: they allow the brain to precisely control the movement without the need for sensory feedback. It is thought that the cerebellum might also encode internal models that reproduce the essential properties of mental representations in the cerebral cortex.

    A computational model of cognitive map structure constituted by a representational geometry model similar to that of a human participant, together with a cognitively plausible grouping mechanism, should be able to not only fit the data of that participant, but to make advance predictions (i.e., to predict which objects will belong together in her cognitive map, based on their features). The chapters in the present volume reflect a commitment to the development of cognitively informed computational treatments of spatial language and spatial representation. Therefore the chapters present computational work, empirical work, or a combination of both.


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Cognitive & Computational Models of Spatial Representation by Patrick Olivier Download PDF EPUB FB2

Therefore the chapters present computational work, empirical work, or a combination of both. The book will appeal to all those interested in spatial language and spatial representation, whether they work in artificial intelligence, cognitive science, cognitive psychology or linguistics.

develop a better appreciation of research into spatial representation by identifying issues that span domain and discipline boundaries; stimulate the discussion of issues in the computational realization of cognitive models of spatial representation.

3. Computational cognitive models of spatial memory Introduction. Computational models attempt to formally describe an aspect (or aspects) of cognition in a simplified fashion, allowing their simulation on computers (McClelland,Sun, b).

Computational cognitive modeling is concerned with achieving a better understanding of Cited by: The purpose of this book is to present current advances in the understanding and modelling of spatial behaviour and language, and the close relationships between cognitive and empirical representations, computational models, and intuitive assistance.

Cognitive representations are studied by the contributions presented in the context of Author: Thora Tenbrink. Computational model is a mathematical model using computation to study complex systems. Typically one sets up a simulation with the desired parameters and lets the computer run.

One then looks at the output to interpret the behavior of the model. Computational cognitive models are computational models used in the field of cognitive science. Lera Boroditsky, in Space, Time and Number in the Brain, Representations of Time in Absolute Space.

Because people tend to recruit spatial representations to think about time, representations of time also differ depending on what spatial representations are most cognitively available to co-opt for time (either in the immediate environment or in the culture more generally) [6,7,9,10,41].

Coping with spatial expressions in a plausible manner is a crucial problem in a number of research fields, specifically cognitive science, artificial intelligence, psychology, and linguistics.

This volume contains a set of theoretical analyses as well as accounts of applications which deal with the problems of representing and processing. Also the Reaction-diffusion principles in non-linear lattices are exploited to develop a compact internal representation of a dynamically changing environment for behavioral planning.

In Part III a software/hardware framework, developed to integrate the insect brain computational model in a simulated/real robotic platform, is illustrated. Biography.

I completed my Ph.D. in Thomas Griffiths’ Computational Cognitive Science Lab formerly at UC Berkeley in August of Prior to completing my Ph.D., I completed an M.S. in Computer Science (EECS), also at UC Berkeley.I am currently at Princeton University working as a visiting postdoctoral researcher in the Computational Cognitive Science Lab.

Advances in Cognitive Neurodynamics: Proceedings of the International Conference on Cognitive Neurodynamics Characterizing Individual Interest by a Computational Model of Reading.

Theta Phase Precession for Spatial Representation in. Learn how to apply cognitive principles to the problems of computer vision. Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to.

A cognitive model is an approximation to animal cognitive processes (predominantly human) for the purposes of comprehension and prediction. Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable.

In contrast to cognitive architectures, cognitive models tend to be focused on a single cognitive phenomenon or process (e. This paper will examine specific problems in spatial cognition where neural networks have been used and have produced plausible models of spatial behavior.

Neural networks have helped in understanding the types of computations that might be performed by the place cells in the hippocampus when the animal moves about and constructs an internal.

The tool uses vector space models together with theory-guided and empirically validated label lists to compute the valence of each word in a text by locating its position in a 2d emotion potential space spanned by the >2 million words of the vector space model.

By means of two computational poetics studies, the author experimentally shows the. Book Description. Coping with spatial expressions in a plausible manner is a crucial problem in a number of research fields, specifically cognitive science, artificial intelligence, psychology, and linguistics.

or other spatial representations, such as intelligent vehicle navigation systems. A Review of Computational Models for Spatial. Computational Brain & Behavior publishes research on the computational basis of the mind.

The journal covers a wide range of topics using mathematical modeling, computer simulation, and empirical work. This journal places a strong emphasis on scientific rigor, and on the greater insights that quantitative modeling can provide. We have built and tested a detailed computational model (implemented in ACT‐R) of visualization accuracy for this task (Lyon et al., ).

The model proposes several processes that operate on chunks representing segments of the path, localized within a cognitive representation of space. In philosophy of mind, the computational theory of mind (CTM), also known as computationalism, is a family of views that hold that the human mind is an information processing system and that cognition and consciousness together are a form of computation.

Warren McCulloch and Walter Pitts () were the first to suggest that neural activity is computational. This book presents the latest findings on head direction cells in a comprehensive treatment that will be a valuable reference for students and researchers in the cognitive sciences, neuroscience, computational science, and robotics.

The book begins by presenting head direction cell properties and an anatomical framework of the head direction. Request PDF | Spatial Cognition, Models of | Neurophysiological research has led to detailed mechanistic theories about how spatial locations and headings are represented in the brain and.

Computational models. If humans reason by building mental models, i.e., mental simulations of situations in the real world, then they should exhibit certain systematic patterns: some inferences should be easy, and others difficult. Cognitive scientists have developed computational models to mimic those patterns across a wide variety of domains.The Conference on Spatial Information Theory – COSIT – grew out of a series of workshops / NATO Advanced Study Institutes / NSF specialist meetings concerned with cognitive and applied aspects of representing large-scale space, particularly geographic space.

In these meetings, the need for a.Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few.