LEADER 00797nam0-22002891i-450- 001 990007089840403321 005 20020606 035 $a000708984 035 $aFED01000708984 035 $a(Aleph)000708984FED01 035 $a000708984 100 $a20020606d1950----km-y0itay50------ba 101 0 $ager 102 $aDE 105 $ay-------001yy 200 1 $aEinführung in die Rechtstheorie$eein Dialog$fvon Ernst von Hippel 205 $a3. durchgearbeitete Aufl. 210 $aKöln$cDeutsche Glocke$d1950 215 $a180 p.$d15 cm 700 1$aHippel,$bErnst : von$0227095 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990007089840403321 952 $aI C 62$b40525$fFGBC 959 $aFGBC 996 $aEinführung in die Rechtstheorie$9704631 997 $aUNINA LEADER 01464nam0 22003493i 450 001 VAN0276140 005 20240521122909.250 017 70$2N$a9783658391799 100 $a20240521d2022 |0itac50 ba 101 $aeng 102 $aDE 105 $a|||| ||||| 200 1 $aGeneric Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling$fSchirin Bär 210 $aWiesbaden$cSpringer Vieweg$d2022 215 $axxii, 148 p.$cill.$d24 cm 610 $aFlexible Manufacturing$9KW:K 610 $aJob Shop Scheduling$9KW:K 610 $aMachine learning$9KW:K 610 $aMulti-Agent System$9KW:K 610 $aProduction Scheduling$9KW:K 610 $aReinforcement Learning$9KW:K 620 $aDE$dWiesbaden$3VANL000457 700 1$aBär$bSchirin$3VANV228837$01261730 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttps://doi.org/10.1007/978-3-658-39179-9$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN0276140 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-Book 8568 $e08eMF8568 20240604 996 $aGeneric Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling$92940556 997 $aUNICAMPANIA