LEADER 01309nam--2200373---450- 001 990003232320203316 005 20090430131718.0 010 $a3-540-08774-5 035 $a000323232 035 $aUSA01000323232 035 $a(ALEPH)000323232USA01 035 $a000323232 100 $a20090430d1980----km-y0itay50------ba 101 $aeng 102 $aIN 105 $aa---||||001yy 200 1 $aLectures on numerical methods for nn-linear varational problems$fR. Glowinski$gNotes by G. Vijayasundaram Adimurthi 210 $aBerlin [etc.]$cSpringer-Verlag$d1980 215 $aVII, 240 p.$cill.$d24 cm 225 2 $aTata Institute of fundamental research lectures on mathematics and physics$v65 300 $aPublished for the Tata Institute of fundamental research 410 0$12001$aTata Institute of fundamental research lectures on mathematics and physics 606 0 $aAnalisi numerica 676 $a511.7 700 1$aGLOWINSKI,$bR.$041336 702 1$aADIMURTHI,$bG. Vijayasundaram 801 0$aIT$bsalbc$gISBD 912 $a990003232320203316 951 $a511.7 GLO$b7769/CBS$c511.7$d00219762 959 $aBK 969 $aSCI 979 $aRSIAV6$b90$c20090430$lUSA01$h1317 996 $aLectures on numerical methods for nn-linear varational problems$91013317 997 $aUNISA LEADER 03554nam 2200469 450 001 9910260595903321 005 20221206094231.0 035 $a(CKB)3860000000003480 035 $a(CaBNVSL)mat07288640 035 $a(IDAMS)0b00006484a5256a 035 $a(IEEE)7288640 035 $a(EXLCZ)993860000000003480 100 $a20151229d2015 uy 101 0 $aeng 135 $aur|n||||||||| 181 $2rdacontent 182 $2isbdmedia 183 $2rdacarrier 200 10$aDecision making under uncertainty $etheory and application /$fMykel J. Kochenderfer, with contributions from Christopher Amato, Girish Chowdhary, Jonathan P. How, Hayley J. Davison Reynolds, Jason R. Thornton, Pedro A. Torres-Carrasquillo, N. Kemal U?re, John Vian 210 1$aCambridge, Massachusetts :$cMIT Press,$d[2015] 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2015] 215 $a1 PDF (xxv, 323 pages) $cillustrations (some color), portraits 225 1 $aLincoln Laboratory series 311 $a0-262-33170-5 320 $aIncludes bibliographical references and index. 330 $aMany important problems involve decision making under uncertainty -- that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance.Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines. 410 0$aLincoln Laboratory series 606 $aIntelligent control systems 606 $aAutomatic machinery 606 $aDecision making$xMathematical models 615 0$aIntelligent control systems. 615 0$aAutomatic machinery. 615 0$aDecision making$xMathematical models. 676 $a003/.56 700 $aKochenderfer$b Mykel J.$f1980-$0848880 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910260595903321 996 $aDecision making under uncertainty$91895943 997 $aUNINA LEADER 02239nam 2200397 450 001 996280789303316 005 20230426071750.0 010 $a1-5090-2523-5 035 $a(CKB)3710000000997608 035 $a(NjHacI)993710000000997608 035 $a(EXLCZ)993710000000997608 100 $a20230426d2016 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) /$fInstitute of Electrical and Electronics Engineers (IEEE) Staff 210 1$aPiscataway, New Jersey :$cInstitute of Electrical and Electronics Engineers (IEEE),$d2016. 215 $a1 online resource (various pagings) $cillustrations 311 $a1-5090-2524-3 330 $aThe DASC is the premier annual conference providing authors an opportunity for publication and presentation to an international audience of papers encompassing the field of avionics systems for aircraft rotorcraft unmanned aircraft (commercial, military, business and general aviation), navigation, communications (all bands voice sensor data), sensors, crew interface, avionics architectures, software, and space and ground components needed for the safe operation of commercial and military aircraft, and space systems Conference papers and plenary presentations cover all aspects of aviation from development, testing, production, to operation and maintenance Avionics sensors embedded in aircraft employing new materials and manufacturing methods and active control computing systems are key contributors to system safety and high aircraft availability Tutorials on highly relevant avionics subjects are offered on two days preceding the technical sessions. 517 $a2016 IEEE/AIAA 35th Digital Avionics Systems Conference 606 $aAir traffic control$vCongresses 606 $aAeronautics$vCongresses 606 $aAvionics$xResearch 615 0$aAir traffic control 615 0$aAeronautics 615 0$aAvionics$xResearch. 676 $a629.13 801 0$bNjHacI 801 1$bNjHacl 906 $aPROCEEDING 912 $a996280789303316 996 $a2016 IEEE$92263651 997 $aUNISA