A Connectionist Model of Spatial Knowledge Acquisition in a Virtual Environment

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Title: A Connectionist Model of Spatial Knowledge Acquisition in a Virtual Environment
Authors: Sas, Corina
O'Hare, G. M. P. (Greg M. P.)
Reilly, Ronan
Permanent link: http://hdl.handle.net/10197/4428
Date: 22-Jun-2003
Abstract: This paper proposes the use of neural networks as a tool for studying navigation within virtual worlds. Results indicate that network learned to predict the next step for a given trajectory, acquiring also basic spatial knowledge in terms of landmarks and configuration of spatial layout. In addition, the network built a spatial representation of the virtual world, e.g. cognitive-like map, which preserves the topology but lacks metric accuracy. The benefits of this approach and the possibility of extending the methodology to the study of navigation in Human Computer Interaction are discussed.
Type of material: Conference Publication
Keywords: NavigationVirtual worlds
Language: en
Status of Item: Peer reviewed
Is part of: Proceedings of MLIRUM'03 Second Workshop on Machine Learning, Information Retrieval and User Modelling, at 9th International Conference Conference on User Modelling, June 22nd-26th, 2003.
Conference Details: MLIRUM'03, Second Workshop on Machine Learning, Information Retrieval and User Modelling, at 9th International Conference on User Modelling, June 22nd-26th, Pittsburgh, PA, USA
Appears in Collections:Computer Science Research Collection

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