NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time

Existing work on automated negotiations has mainly focused on bilateral negotiations with linear utility functions. It is often assumed that all possible agreements and their utility values are given beforehand. Most real-world negotiations however are much more complex. We introduce a new family of...

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Detalhes bibliográficos
Autores: De Jonge, Dave, Sierra, Carles
Tipo de documento: artigo
Estado:Versión aceptada para publicación
Data de publicação:2015
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositório:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/130274
Acesso em linha:http://hdl.handle.net/10261/130274
Access Level:Acceso aberto
Palavra-chave:Traveling salesman problem
Non-linear utility
Negotiating Salesmen Problem
Heuristic algorithms
Negotiation
Multilateral
Search
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spelling NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited TimeDe Jonge, DaveSierra, CarlesTraveling salesman problemNon-linear utilityNegotiating Salesmen ProblemHeuristic algorithmsNegotiationMultilateralSearchExisting work on automated negotiations has mainly focused on bilateral negotiations with linear utility functions. It is often assumed that all possible agreements and their utility values are given beforehand. Most real-world negotiations however are much more complex. We introduce a new family of negotiation algorithms that is applicable to domains with many agents, an intractably large space of possible agreements, non-linear utility functions and limited time so an exhaustive search for the best proposals is not feasible. We assume that agents are selfish and cannot be blindly trusted, so the algorithm does not rely on any mediator. This family of algorithms is called $$\hbox {NB}^{3}$$NB3 and applies heuristic Branch & Bound search to find good proposals. Search and negotiation happen simultaneously and therefore strongly influence each other. It applies a new time-based negotiation strategy that considers two utility aspiration levels: one for the agent itself and one for its opponents. Also, we introduce a negotiation protocol that imposes almost no restrictions and is therefore better applicable to negotiations with humans. We present the Negotiating Salesmen Problem (NSP): a variant of the Traveling Salesman Problem with multiple negotiating agents, as a test case. We describe an implementation of $$\hbox {NB}^{3}$$NB3 designed for the NSP and present the results of experiments with this implementation. We conclude that the algorithm is able to decrease the costs of the agents significantly, that the heuristic search is efficient and that the algorithm scales well with increasing complexity of the problem. © 2014, The Author(s).Supported by the Agreement Technologies CONSOLIDER project, contract CSD2007-0022 and INGENIO 2010 and CHIST-ERA project ACE and the Spanish Ministry of Education and Science TIN2010-16306 project CBIT and EU project 318770 PRAISE and Project PACES; EPSRC EP/J012149/1Peer ReviewedKluwer Academic PublishersMinisterio de Economía y Competitividad (España)European CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2016201620152016info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/130274reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/FP7/318770Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1302742026-05-22T06:33:51Z
dc.title.none.fl_str_mv NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
title NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
spellingShingle NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
De Jonge, Dave
Traveling salesman problem
Non-linear utility
Negotiating Salesmen Problem
Heuristic algorithms
Negotiation
Multilateral
Search
title_short NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
title_full NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
title_fullStr NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
title_full_unstemmed NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
title_sort NB3: a Multilateral Negotiation Algorithm for Large, Non-linear Agreement Spaces with Limited Time
dc.creator.none.fl_str_mv De Jonge, Dave
Sierra, Carles
author De Jonge, Dave
author_facet De Jonge, Dave
Sierra, Carles
author_role author
author2 Sierra, Carles
author2_role author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (España)
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Traveling salesman problem
Non-linear utility
Negotiating Salesmen Problem
Heuristic algorithms
Negotiation
Multilateral
Search
topic Traveling salesman problem
Non-linear utility
Negotiating Salesmen Problem
Heuristic algorithms
Negotiation
Multilateral
Search
description Existing work on automated negotiations has mainly focused on bilateral negotiations with linear utility functions. It is often assumed that all possible agreements and their utility values are given beforehand. Most real-world negotiations however are much more complex. We introduce a new family of negotiation algorithms that is applicable to domains with many agents, an intractably large space of possible agreements, non-linear utility functions and limited time so an exhaustive search for the best proposals is not feasible. We assume that agents are selfish and cannot be blindly trusted, so the algorithm does not rely on any mediator. This family of algorithms is called $$\hbox {NB}^{3}$$NB3 and applies heuristic Branch & Bound search to find good proposals. Search and negotiation happen simultaneously and therefore strongly influence each other. It applies a new time-based negotiation strategy that considers two utility aspiration levels: one for the agent itself and one for its opponents. Also, we introduce a negotiation protocol that imposes almost no restrictions and is therefore better applicable to negotiations with humans. We present the Negotiating Salesmen Problem (NSP): a variant of the Traveling Salesman Problem with multiple negotiating agents, as a test case. We describe an implementation of $$\hbox {NB}^{3}$$NB3 designed for the NSP and present the results of experiments with this implementation. We conclude that the algorithm is able to decrease the costs of the agents significantly, that the heuristic search is efficient and that the algorithm scales well with increasing complexity of the problem. © 2014, The Author(s).
publishDate 2015
dc.date.none.fl_str_mv 2015
2016
2016
2016
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/10261/130274
url http://hdl.handle.net/10261/130274
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/FP7/318770
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Kluwer Academic Publishers
publisher.none.fl_str_mv Kluwer Academic Publishers
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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