Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm

This paper proposes a new Case-Based Reasoning (CBR) approach, named Q-CBR, that uses a Qualitative Spatial Reasoning theory to model, retrieve and reuse cases by means of spatial relations. A qualitative distance and orientation calculus (EOPRA) is used to model cases using qualitative relations be...

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Detalles Bibliográficos
Autores: Homem, Thiago, Perico, Danilo H., Santos, Paulo H., Bianchi, Reinaldo, López de Mántaras, Ramón
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2016
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/157270
Acceso en línea:http://hdl.handle.net/10261/157270
Access Level:acceso abierto
Palabra clave:Humanoid robots
Qualitative spatial reasoning
Case-based reasoning
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spelling Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithmHomem, ThiagoPerico, Danilo H.Santos, Paulo H.Bianchi, ReinaldoLópez de Mántaras, RamónHumanoid robotsQualitative spatial reasoningCase-based reasoningThis paper proposes a new Case-Based Reasoning (CBR) approach, named Q-CBR, that uses a Qualitative Spatial Reasoning theory to model, retrieve and reuse cases by means of spatial relations. A qualitative distance and orientation calculus (EOPRA) is used to model cases using qualitative relations between the objects in a case. A new retrieval algorithm is proposed that uses the Conceptual Neighborhood Diagram to compute the similarity measure between a new problem and the cases in the case base. A reuse algorithm is also introduced that selects the most similar case and shares it with other agents, based on their qualitative position. The proposed approach was evaluated on simulation and on real humanoid robots. Preliminary results suggest that the proposed approach is faster than using a quantitative model and other similarity measure such as the Euclidean distance. As a result of running Q-CBR, the robots obtained a higher average number of goals than those obtained when running a metric CBR approach.Peer ReviewedSpringer NatureConsejo Superior de Investigaciones Científicas (España)Generalitat de CatalunyaConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2017201720162017info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/157270reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1572702026-05-22T06:33:51Z
dc.title.none.fl_str_mv Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
title Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
spellingShingle Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
Homem, Thiago
Humanoid robots
Qualitative spatial reasoning
Case-based reasoning
title_short Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
title_full Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
title_fullStr Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
title_full_unstemmed Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
title_sort Qualitative Case-based Reasoning for Humanoid Robot Soccer: a new retrieval and reuse algorithm
dc.creator.none.fl_str_mv Homem, Thiago
Perico, Danilo H.
Santos, Paulo H.
Bianchi, Reinaldo
López de Mántaras, Ramón
author Homem, Thiago
author_facet Homem, Thiago
Perico, Danilo H.
Santos, Paulo H.
Bianchi, Reinaldo
López de Mántaras, Ramón
author_role author
author2 Perico, Danilo H.
Santos, Paulo H.
Bianchi, Reinaldo
López de Mántaras, Ramón
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas (España)
Generalitat de Catalunya
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Humanoid robots
Qualitative spatial reasoning
Case-based reasoning
topic Humanoid robots
Qualitative spatial reasoning
Case-based reasoning
description This paper proposes a new Case-Based Reasoning (CBR) approach, named Q-CBR, that uses a Qualitative Spatial Reasoning theory to model, retrieve and reuse cases by means of spatial relations. A qualitative distance and orientation calculus (EOPRA) is used to model cases using qualitative relations between the objects in a case. A new retrieval algorithm is proposed that uses the Conceptual Neighborhood Diagram to compute the similarity measure between a new problem and the cases in the case base. A reuse algorithm is also introduced that selects the most similar case and shares it with other agents, based on their qualitative position. The proposed approach was evaluated on simulation and on real humanoid robots. Preliminary results suggest that the proposed approach is faster than using a quantitative model and other similarity measure such as the Euclidean distance. As a result of running Q-CBR, the robots obtained a higher average number of goals than those obtained when running a metric CBR approach.
publishDate 2016
dc.date.none.fl_str_mv 2016
2017
2017
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/157270
url http://hdl.handle.net/10261/157270
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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