An ACS cooperative learning approach for route finding in natural environment

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An ACS cooperative learning approach for route finding in natural environment

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Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents

Irvine, California

SESSION: Route finding and road networks table of contents

Article No. 13

Year of Publication: 2008

ISBN:978-1-60558-323-5

Authors

David Brosset	Naval Academy Research Institute, Brest Naval, France
Christophe Claramunt	Naval Academy Research Institute, Brest Naval, France
Eric Saux	Naval Academy Research Institute, Brest Naval, France

Sponsors

: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft

Publisher

ACM New York, NY, USA

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ABSTRACT

This paper introduces an ant-based colony system for the representation of a verbal route description. It is grounded on a natural metaphor that mimics the behavior of ant colonies. While conventional ant-based algorithms are based on the optimization of path strategies on an existing network, the approach presented in this paper differs in the way the network is dynamically derived during the optimization process, and evaluated according to its degree of match regarding the semantics exhibited by a verbal route description. The algorithm is applied to a route searching process in a natural environment, and studied in terms of its performance capabilities.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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