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dc.contributor.authorSayama, H.
dc.contributor.authorBar-Yam, Y.
dc.contributor.authorKlein, Mark
dc.contributor.authorFaratin, Peyman
dc.date.accessioned2018-02-16T16:00:33Z
dc.date.available2018-02-16T16:00:33Z
dc.date.issued2003
dc.identifier.issn1541-1672
dc.identifier.urihttp://hdl.handle.net/1721.1/113705
dc.description.abstractResearch to date on negotiation protocols has focused almost exclusively on defining simple contracts consisting of one or a few independent issues and a relatively small number of possible contracts. Many real-world contracts, in contrast, are much more complex, consisting of multiple interdependent issues and intractably large contract spaces. The family of negotiation protocols we've developed make substantial progress toward achieving near-optimal outcomes for negotiations with binary issue dependencies. We propose a simulated annealing-based approach, a refined version based on a parity-maintaining annealing mediator, and an unmediated version of the negotiation protocol. Keywords: protocols; contracts; proposals; simulated annealing; hamming distance; pareto optimization; aggregates; utility theory, software agents, contracts, simulated annealing; utility function; negotiation protocols; contract; binary issue dependency; simulated annealing-based approach; parity-maintaining annealing mediator; software agenten_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/MIS.2003.1249167en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceKleinen_US
dc.titleProtocols for negotiating complex contractsen_US
dc.typeArticleen_US
dc.identifier.citationKlein, M. et al. “Protocols for Negotiating Complex Contracts.” IEEE Intelligent Systems 18, 6 (November 2003): 32–38 © 2003 IEEEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor.departmentSloan School of Management
dc.contributor.departmentMassachusetts Institute of Technology. Center for Collective Intelligence
dc.contributor.approverKlein, Marken_US
dc.contributor.mitauthorKlein, Mark
dc.contributor.mitauthorFaratin, Peyman
dc.relation.journalIEEE Intelligent Systemsen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsKlein, M.; Faratin, P.; Sayama, H.; Bar-Yam, Y.en_US
dspace.embargo.termsNen_US
mit.licensePUBLISHER_POLICYen_US


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