Matches in SemOpenAlex for { <https://semopenalex.org/work/W2011911409> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2011911409 abstract "Many tracking and guidance problems may be formulated as a terminating stochastic game in which the distribution of outcomes is affected by the intermediate actions. Traditional technique ignore this interaction. In this paper we develop an information gathering strategy which maximizes the expected gain of the outcome. For example, the objective could be a function of the terminal miss distance and target identify with penalties for missing a valid target or attacking a friendly one. Several trade-offs are addressed: the increased information available from taking more measurements, the fact that an increased number of measurement may adversely affect change of success and the fact that later measurements may be more informative but also may be of little use since there my not be enough time available for reaction to this extra information. The problem is formulated so that we are required to choose, under uncertainty, an alternative from a set of possible decisions. This set has a discrete uncertainty as to the number of measurements to be taken and a continuous uncertainty as to where and when the measurements should be taken. Preferences over consequences are modeled with a utility function. We propose to choose as optimal the alternative which maximizes expected utility. A simulation based approximation to the solution of this stochastic optimization problem is outlined. This relies on recent developments in dimensions swapping Markov Chain Monte Carlo (MCMC) techniques. The use of MCMC methodology allow us to explore the expected utility surface and thus select a measurement strategy. The resulting algorithm is demonstrated on a simple guidance problem." @default.
- W2011911409 created "2016-06-24" @default.
- W2011911409 creator A5021215761 @default.
- W2011911409 creator A5086686713 @default.
- W2011911409 date "1998-09-03" @default.
- W2011911409 modified "2023-09-23" @default.
- W2011911409 title "<title>Bayesian sensor resource allocation</title>" @default.
- W2011911409 doi "https://doi.org/10.1117/12.324632" @default.
- W2011911409 hasPublicationYear "1998" @default.
- W2011911409 type Work @default.
- W2011911409 sameAs 2011911409 @default.
- W2011911409 citedByCount "3" @default.
- W2011911409 countsByYear W20119114092013 @default.
- W2011911409 crossrefType "proceedings-article" @default.
- W2011911409 hasAuthorship W2011911409A5021215761 @default.
- W2011911409 hasAuthorship W2011911409A5086686713 @default.
- W2011911409 hasConcept C105795698 @default.
- W2011911409 hasConcept C107673813 @default.
- W2011911409 hasConcept C111350023 @default.
- W2011911409 hasConcept C119857082 @default.
- W2011911409 hasConcept C126255220 @default.
- W2011911409 hasConcept C14036430 @default.
- W2011911409 hasConcept C144237770 @default.
- W2011911409 hasConcept C148220186 @default.
- W2011911409 hasConcept C149441793 @default.
- W2011911409 hasConcept C154945302 @default.
- W2011911409 hasConcept C177142836 @default.
- W2011911409 hasConcept C177264268 @default.
- W2011911409 hasConcept C199360897 @default.
- W2011911409 hasConcept C200594392 @default.
- W2011911409 hasConcept C206345919 @default.
- W2011911409 hasConcept C29202148 @default.
- W2011911409 hasConcept C31258907 @default.
- W2011911409 hasConcept C33923547 @default.
- W2011911409 hasConcept C41008148 @default.
- W2011911409 hasConcept C73795354 @default.
- W2011911409 hasConcept C78458016 @default.
- W2011911409 hasConcept C86803240 @default.
- W2011911409 hasConcept C98763669 @default.
- W2011911409 hasConceptScore W2011911409C105795698 @default.
- W2011911409 hasConceptScore W2011911409C107673813 @default.
- W2011911409 hasConceptScore W2011911409C111350023 @default.
- W2011911409 hasConceptScore W2011911409C119857082 @default.
- W2011911409 hasConceptScore W2011911409C126255220 @default.
- W2011911409 hasConceptScore W2011911409C14036430 @default.
- W2011911409 hasConceptScore W2011911409C144237770 @default.
- W2011911409 hasConceptScore W2011911409C148220186 @default.
- W2011911409 hasConceptScore W2011911409C149441793 @default.
- W2011911409 hasConceptScore W2011911409C154945302 @default.
- W2011911409 hasConceptScore W2011911409C177142836 @default.
- W2011911409 hasConceptScore W2011911409C177264268 @default.
- W2011911409 hasConceptScore W2011911409C199360897 @default.
- W2011911409 hasConceptScore W2011911409C200594392 @default.
- W2011911409 hasConceptScore W2011911409C206345919 @default.
- W2011911409 hasConceptScore W2011911409C29202148 @default.
- W2011911409 hasConceptScore W2011911409C31258907 @default.
- W2011911409 hasConceptScore W2011911409C33923547 @default.
- W2011911409 hasConceptScore W2011911409C41008148 @default.
- W2011911409 hasConceptScore W2011911409C73795354 @default.
- W2011911409 hasConceptScore W2011911409C78458016 @default.
- W2011911409 hasConceptScore W2011911409C86803240 @default.
- W2011911409 hasConceptScore W2011911409C98763669 @default.
- W2011911409 hasLocation W20119114091 @default.
- W2011911409 hasOpenAccess W2011911409 @default.
- W2011911409 hasPrimaryLocation W20119114091 @default.
- W2011911409 hasRelatedWork W2011083491 @default.
- W2011911409 hasRelatedWork W2020176575 @default.
- W2011911409 hasRelatedWork W2031482861 @default.
- W2011911409 hasRelatedWork W2143203814 @default.
- W2011911409 hasRelatedWork W2373137553 @default.
- W2011911409 hasRelatedWork W3010526228 @default.
- W2011911409 hasRelatedWork W3121431328 @default.
- W2011911409 hasRelatedWork W3123491991 @default.
- W2011911409 hasRelatedWork W3123569033 @default.
- W2011911409 hasRelatedWork W38807639 @default.
- W2011911409 isParatext "false" @default.
- W2011911409 isRetracted "false" @default.
- W2011911409 magId "2011911409" @default.
- W2011911409 workType "article" @default.