Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-25510-6-23
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dc.titleThe complexity of approximate Nash equilibrium in congestion games with negative delays
dc.contributor.authorMagniez, F.
dc.contributor.authorDe Rougemont, M.
dc.contributor.authorSantha, M.
dc.contributor.authorZeitoun, X.
dc.date.accessioned2014-12-12T07:54:09Z
dc.date.available2014-12-12T07:54:09Z
dc.date.issued2011
dc.identifier.citationMagniez, F.,De Rougemont, M.,Santha, M.,Zeitoun, X. (2011). The complexity of approximate Nash equilibrium in congestion games with negative delays. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7090 LNCS : 266-277. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-25510-6-23" target="_blank">https://doi.org/10.1007/978-3-642-25510-6-23</a>
dc.identifier.isbn9783642255090
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/116790
dc.description.abstractWe extend the study of the complexity of computing an ε-approximate Nash equilibrium in symmetric congestion games from the case of positive delay functions to delays of arbitrary sign. Our results show that with this extension the complexity has a richer structure, and it depends on the exact nature of the signs allowed. We first prove that in symmetric games with increasing delay functions and with α-bounded jump the ε-Nash dynamic converges in polynomial time when all delays are negative, similarly to the case of positive delays. We are able to extend this result to monotone delay functions. We then establish a hardness result for symmetric games with increasing delay functions and with α-bounded jump when the delays can be both positive and negative: in that case computing an ε-approximate Nash equilibrium becomes PLS-complete, even if each delay function is of constant sign or of constant absolute value. © 2011 Springer-Verlag Berlin Heidelberg.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-25510-6-23
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCENTRE FOR QUANTUM TECHNOLOGIES
dc.description.doi10.1007/978-3-642-25510-6-23
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume7090 LNCS
dc.description.page266-277
dc.identifier.isiutNOT_IN_WOS
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