
Slide

Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Davoust, A.; Floyd, M. W.; Esfandiari, B.
Use of fuzzy histograms to model the spatial distribution of objects in case-based reasoning Article de journal
Dans: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5032 LNAI, p. 72–83, 2008, ISSN: 03029743, (ISBN: 3540688218; 9783540688211 Place: Windsor).
Résumé | Liens | BibTeX | Étiquettes: Ad hoc networks, Case based reasoning, Computer Simulation, Fuzzy Histograms, Fuzzy logic, Fuzzy sets, Mathematical models, Soccer Simulation, Software agents
@article{davoust_use_2008,
title = {Use of fuzzy histograms to model the spatial distribution of objects in case-based reasoning},
author = {A. Davoust and M. W. Floyd and B. Esfandiari},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-44649181663&doi=10.1007%2f978-3-540-68825-9_8&partnerID=40&md5=2d0164da55518a67bd43a88e53bf4afc},
doi = {10.1007/978-3-540-68825-9_8},
issn = {03029743},
year = {2008},
date = {2008-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {5032 LNAI},
pages = {72–83},
abstract = {In the context of the RoboCup Simulation League, we describe a new representation of a software agent's visual perception ("scene"), well suited for case-based reasoning. Most existing representations use either heterogeneous, manually selected features of the scene, or the raw list of visible objects, and use ad hoc similarity measures for CBR. Our representation is based on histograms of objects over a partition of the scene space. This method transforms a list of objects into an image-like representation with customizable granularity, and uses fuzzy logic to smoothen boundary effects of the partition. We also introduce a new similarity metric based on the Jaccard Coefficient, to compare scenes represented by such histograms. We present our implementation of this approach in a case-based reasoning project, and experimental results showing highly efficient scene comparison. © 2008 Springer-Verlag Berlin Heidelberg.},
note = {ISBN: 3540688218; 9783540688211
Place: Windsor},
keywords = {Ad hoc networks, Case based reasoning, Computer Simulation, Fuzzy Histograms, Fuzzy logic, Fuzzy sets, Mathematical models, Soccer Simulation, Software agents},
pubstate = {published},
tppubtype = {article}
}
In the context of the RoboCup Simulation League, we describe a new representation of a software agent's visual perception ("scene"), well suited for case-based reasoning. Most existing representations use either heterogeneous, manually selected features of the scene, or the raw list of visible objects, and use ad hoc similarity measures for CBR. Our representation is based on histograms of objects over a partition of the scene space. This method transforms a list of objects into an image-like representation with customizable granularity, and uses fuzzy logic to smoothen boundary effects of the partition. We also introduce a new similarity metric based on the Jaccard Coefficient, to compare scenes represented by such histograms. We present our implementation of this approach in a case-based reasoning project, and experimental results showing highly efficient scene comparison. © 2008 Springer-Verlag Berlin Heidelberg.