Using genetic algorithms to create solutions for conflict resolution
Main Author: | |
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Publication Date: | 2013 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/1822/26558 |
Summary: | The process of devising solutions for conflict resolution generally configures a challenging task. There exist different approaches to address the problem, namely the use of case-based models or even relying on the parties themselves to perform the task. From a computational point of view, these problems generally represent a NP-complete problem. In order to surpass this shortcoming, in this paper it is presented a biologically inspired method to deal with the problem in which genetic algorithms are used to create possible solutions for a given dispute. The approach presented is able to generate a broad number of diverse solutions that cover virtually the whole search space for a given problem. This approach provides better results than a case-based approach since: (1) it is independent of the legal domain and (2) it does not depend on the number and quality of cases present in a database. The results of this work are being applied in a negotiation tool that is part of the UMCourt conflict resolution platform. |
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Using genetic algorithms to create solutions for conflict resolutionGenetic algorithmsNegotiationOnline dispute resolutionIntelligent environmentsScience & TechnologyThe process of devising solutions for conflict resolution generally configures a challenging task. There exist different approaches to address the problem, namely the use of case-based models or even relying on the parties themselves to perform the task. From a computational point of view, these problems generally represent a NP-complete problem. In order to surpass this shortcoming, in this paper it is presented a biologically inspired method to deal with the problem in which genetic algorithms are used to create possible solutions for a given dispute. The approach presented is able to generate a broad number of diverse solutions that cover virtually the whole search space for a given problem. This approach provides better results than a case-based approach since: (1) it is independent of the legal domain and (2) it does not depend on the number and quality of cases present in a database. The results of this work are being applied in a negotiation tool that is part of the UMCourt conflict resolution platform.The work described here was developed under the TIARAC-Telematics and Artificial Intelligence in Alternative Conflict Resolution research project (PTDC/JUR/71354/2006), a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro was supported by a doctoral grant, also by FCT (SFRH/BD/64890/2009).ElsevierUniversidade do MinhoCarneiro, Davide RuaNovais, PauloNeves, José20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/26558eng0925-231210.1016/j.neucom.2012.03.024http://dx.doi.org/10.1016/j.neucom.2012.03.024info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-12T05:15:12Zoai:repositorium.sdum.uminho.pt:1822/26558Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:17:03.698420Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Using genetic algorithms to create solutions for conflict resolution |
title |
Using genetic algorithms to create solutions for conflict resolution |
spellingShingle |
Using genetic algorithms to create solutions for conflict resolution Carneiro, Davide Rua Genetic algorithms Negotiation Online dispute resolution Intelligent environments Science & Technology |
title_short |
Using genetic algorithms to create solutions for conflict resolution |
title_full |
Using genetic algorithms to create solutions for conflict resolution |
title_fullStr |
Using genetic algorithms to create solutions for conflict resolution |
title_full_unstemmed |
Using genetic algorithms to create solutions for conflict resolution |
title_sort |
Using genetic algorithms to create solutions for conflict resolution |
author |
Carneiro, Davide Rua |
author_facet |
Carneiro, Davide Rua Novais, Paulo Neves, José |
author_role |
author |
author2 |
Novais, Paulo Neves, José |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Carneiro, Davide Rua Novais, Paulo Neves, José |
dc.subject.por.fl_str_mv |
Genetic algorithms Negotiation Online dispute resolution Intelligent environments Science & Technology |
topic |
Genetic algorithms Negotiation Online dispute resolution Intelligent environments Science & Technology |
description |
The process of devising solutions for conflict resolution generally configures a challenging task. There exist different approaches to address the problem, namely the use of case-based models or even relying on the parties themselves to perform the task. From a computational point of view, these problems generally represent a NP-complete problem. In order to surpass this shortcoming, in this paper it is presented a biologically inspired method to deal with the problem in which genetic algorithms are used to create possible solutions for a given dispute. The approach presented is able to generate a broad number of diverse solutions that cover virtually the whole search space for a given problem. This approach provides better results than a case-based approach since: (1) it is independent of the legal domain and (2) it does not depend on the number and quality of cases present in a database. The results of this work are being applied in a negotiation tool that is part of the UMCourt conflict resolution platform. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 2013-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/26558 |
url |
https://hdl.handle.net/1822/26558 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0925-2312 10.1016/j.neucom.2012.03.024 http://dx.doi.org/10.1016/j.neucom.2012.03.024 |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
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