Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/123456789/634
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dc.contributor.authorRavikumar, Ken_US
dc.contributor.authorDiatha, Krishna Sundar-
dc.date.accessioned2012-07-26T11:27:42Z-
dc.date.accessioned2016-01-01T07:15:08Z-
dc.date.accessioned2019-05-27T08:37:45Z-
dc.date.available2012-07-26T11:27:42Z-
dc.date.available2016-01-01T07:15:08Z-
dc.date.available2019-05-27T08:37:45Z-
dc.date.copyright2003en_US
dc.date.issued2003-
dc.identifier.otherWP_IIMB_210-
dc.identifier.urihttp://repository.iimb.ac.in/handle/123456789/634-
dc.description.abstractWe study price dynamics in a service market environment where identical service providers dynamically reset their prices to price discriminate informed and uninformed consumers. A semi-Markovian game model for dynamic pricing is developed and a new multi-time scale actor-critic algorithm is proposed for multi-agent reinforcement learning. Also, experimental results on convergence to a Nash equilibrium are presented.-
dc.language.isoenen_US
dc.publisherIndian Institute of Management Bangalore-
dc.relation.ispartofseriesIIMB Working Paper-210-
dc.subjectService market environment-
dc.subjectGame model-
dc.subjectDynamic pricing-
dc.titleMulti-agent learning in dynamic pricing games of service marketsen_US
dc.typeWorking Paper-
dc.pages25p.-
dc.identifier.accessionE23124-
Appears in Collections:2003
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