A multi-agent system for electronic commerce including adaptive strategic behaviours
Autor(a) principal: | |
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Data de Publicação: | 1999 |
Outros Autores: | , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://repositorio-aberto.up.pt/handle/10216/74300 |
Resumo: | This work is primarily based on the use of software agents forautomated negotiation. We present in this paper a test-bed for agents in anelectronic marketplace, through which we simulated different scenariosallowing us to evaluate different agents negotiation behaviours. The systemfollows a multi-party and multi-issue negotiation approach. We tested thesystem by comparing the performance of agents that use multiple tactics withones that include learning capabilities based on a specific kind ofReinforcement Learning technique. First experiments showed that the adaptiveagents tend to win deals over their competitors as their experience increases. |
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A multi-agent system for electronic commerce including adaptive strategic behavioursInformática, Ciências da computação e da informaçãoInformatics, Computer and information sciencesThis work is primarily based on the use of software agents forautomated negotiation. We present in this paper a test-bed for agents in anelectronic marketplace, through which we simulated different scenariosallowing us to evaluate different agents negotiation behaviours. The systemfollows a multi-party and multi-issue negotiation approach. We tested thesystem by comparing the performance of agents that use multiple tactics withones that include learning capabilities based on a specific kind ofReinforcement Learning technique. First experiments showed that the adaptiveagents tend to win deals over their competitors as their experience increases.19991999-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/74300eng10.1007/3-540-48159-1_18Eugénio OliveiraHenrique Lopes CardosoMax Schaeferinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T12:25:53Zoai:repositorio-aberto.up.pt:10216/74300Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:20:13.496050Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
title |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
spellingShingle |
A multi-agent system for electronic commerce including adaptive strategic behaviours Eugénio Oliveira Informática, Ciências da computação e da informação Informatics, Computer and information sciences |
title_short |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
title_full |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
title_fullStr |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
title_full_unstemmed |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
title_sort |
A multi-agent system for electronic commerce including adaptive strategic behaviours |
author |
Eugénio Oliveira |
author_facet |
Eugénio Oliveira Henrique Lopes Cardoso Max Schaefer |
author_role |
author |
author2 |
Henrique Lopes Cardoso Max Schaefer |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Eugénio Oliveira Henrique Lopes Cardoso Max Schaefer |
dc.subject.por.fl_str_mv |
Informática, Ciências da computação e da informação Informatics, Computer and information sciences |
topic |
Informática, Ciências da computação e da informação Informatics, Computer and information sciences |
description |
This work is primarily based on the use of software agents forautomated negotiation. We present in this paper a test-bed for agents in anelectronic marketplace, through which we simulated different scenariosallowing us to evaluate different agents negotiation behaviours. The systemfollows a multi-party and multi-issue negotiation approach. We tested thesystem by comparing the performance of agents that use multiple tactics withones that include learning capabilities based on a specific kind ofReinforcement Learning technique. First experiments showed that the adaptiveagents tend to win deals over their competitors as their experience increases. |
publishDate |
1999 |
dc.date.none.fl_str_mv |
1999 1999-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio-aberto.up.pt/handle/10216/74300 |
url |
https://repositorio-aberto.up.pt/handle/10216/74300 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1007/3-540-48159-1_18 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799135501769244672 |