Non-Standard Optimality Criteria for Stochastic Control Problems

Simple item page
dc.contributor.authorFernandez-Gaucherand, Emmanuelen_US
dc.contributor.authorMarcus, Steven I.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:59:58Z
dc.date.available2007-05-23T09:59:58Z
dc.date.issued1995en_US
dc.description.abstractIn this paper, we survey several recent developments on non- standard optimality criteria for controlled Markov process models of stochastic control problems. Commonly, the criteria employed for optimal decision and control are either the discounted cost (DC) or the long-run average cost (AC). We present results on several other criteria that, as opposed to the AC or DC, take into account, e.g., a) the variance of costs; b) multiple objectives; c) robustness with respect to sample path realizations; d) sensitivity to long but finite horizon performance as well as long-run average performance.en_US
dc.format.extent393395 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5682
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1995-101en_US
dc.subjectstochastic systemsen_US
dc.subjectstochastic control en_US
dc.subjectmarkov decision processesen_US
dc.subjectSystems Integration Methodologyen_US
dc.titleNon-Standard Optimality Criteria for Stochastic Control Problemsen_US
dc.typeTechnical Reporten_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
TR_95-101.pdf
Size:
384.17 KB
Format:
Adobe Portable Document Format
Download

Collections

Institute for Systems Research Technical Reports