Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments.
- Autores
- De La Rosa, Josep Lluis; Hormazábal, Nicolás; Aciar, Silvana Vanesa; Lopardo, Gabriel Alejandro; Trias, Albert; Montaner, Miquel
- Año de publicación
- 2011
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies.
Fil: De La Rosa, Josep Lluis. Universidad de Girona; España
Fil: Hormazábal, Nicolás. Universidad de Girona; España
Fil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Lopardo, Gabriel Alejandro. Universidad de Girona; España
Fil: Trias, Albert. Universidad de Girona; España
Fil: Montaner, Miquel. No especifíca; - Materia
-
AGENTS
RECOMMENDER SYSTEMS - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/196381
Ver los metadatos del registro completo
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Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments.De La Rosa, Josep LluisHormazábal, NicolásAciar, Silvana VanesaLopardo, Gabriel AlejandroTrias, AlbertMontaner, MiquelAGENTSRECOMMENDER SYSTEMShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies.Fil: De La Rosa, Josep Lluis. Universidad de Girona; EspañaFil: Hormazábal, Nicolás. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Lopardo, Gabriel Alejandro. Universidad de Girona; EspañaFil: Trias, Albert. Universidad de Girona; EspañaFil: Montaner, Miquel. No especifíca;Institute of Electrical and Electronics Engineers2011-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/196381De La Rosa, Josep Lluis; Hormazábal, Nicolás; Aciar, Silvana Vanesa; Lopardo, Gabriel Alejandro; Trias, Albert; et al.; Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments.; Institute of Electrical and Electronics Engineers; Ieee Transactions On Industrial Electronics; 58; 6; 7-2011; 2073-20850278-0046CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/5175290info:eu-repo/semantics/altIdentifier/doi/10.1109/TIE.2009.2027917info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:02:16Zoai:ri.conicet.gov.ar:11336/196381instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:02:17.142CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
title |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
spellingShingle |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. De La Rosa, Josep Lluis AGENTS RECOMMENDER SYSTEMS |
title_short |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
title_full |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
title_fullStr |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
title_full_unstemmed |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
title_sort |
Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments. |
dc.creator.none.fl_str_mv |
De La Rosa, Josep Lluis Hormazábal, Nicolás Aciar, Silvana Vanesa Lopardo, Gabriel Alejandro Trias, Albert Montaner, Miquel |
author |
De La Rosa, Josep Lluis |
author_facet |
De La Rosa, Josep Lluis Hormazábal, Nicolás Aciar, Silvana Vanesa Lopardo, Gabriel Alejandro Trias, Albert Montaner, Miquel |
author_role |
author |
author2 |
Hormazábal, Nicolás Aciar, Silvana Vanesa Lopardo, Gabriel Alejandro Trias, Albert Montaner, Miquel |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
AGENTS RECOMMENDER SYSTEMS |
topic |
AGENTS RECOMMENDER SYSTEMS |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies. Fil: De La Rosa, Josep Lluis. Universidad de Girona; España Fil: Hormazábal, Nicolás. Universidad de Girona; España Fil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina Fil: Lopardo, Gabriel Alejandro. Universidad de Girona; España Fil: Trias, Albert. Universidad de Girona; España Fil: Montaner, Miquel. No especifíca; |
description |
The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-07 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/196381 De La Rosa, Josep Lluis; Hormazábal, Nicolás; Aciar, Silvana Vanesa; Lopardo, Gabriel Alejandro; Trias, Albert; et al.; Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments.; Institute of Electrical and Electronics Engineers; Ieee Transactions On Industrial Electronics; 58; 6; 7-2011; 2073-2085 0278-0046 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/196381 |
identifier_str_mv |
De La Rosa, Josep Lluis; Hormazábal, Nicolás; Aciar, Silvana Vanesa; Lopardo, Gabriel Alejandro; Trias, Albert; et al.; Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments.; Institute of Electrical and Electronics Engineers; Ieee Transactions On Industrial Electronics; 58; 6; 7-2011; 2073-2085 0278-0046 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/5175290 info:eu-repo/semantics/altIdentifier/doi/10.1109/TIE.2009.2027917 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers |
publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844613825340375040 |
score |
13.070432 |