LEADER 01642nam0 22003733i 450 001 VAN00276141 005 20240806101544.396 017 70$2N$a9783658376161 100 $a20240521d2022 |0itac50 ba 101 $aeng 102 $aDE 105 $a|||| ||||| 200 1 $aReinforcement Learning with Hybrid Quantum Approximation in the NISQ Context$fLeonhard Kunczik 210 $aWiesbaden$cSpringer Vieweg$d2022 215 $axviii, 134 p.$cill.$d24 cm 606 $a68-XX$xComputer science [MSC 2020]$3VANC019670$2MF 606 $a81-XX$xQuantum theory [MSC 2020]$3VANC019967$2MF 606 $a97-XX$xMathematics education [MSC 2020]$3VANC023813$2MF 610 $aAttacker-Defender Scenarios$9KW:K 610 $aQuanten Computing$9KW:K 610 $aQuantum Reinforcement Learning$9KW:K 610 $aQuantum machine learning$9KW:K 610 $aReinforcement Learning$9KW:K 620 $aDE$dWiesbaden$3VANL000457 700 1$aKunczik$bLeonhard$3VANV228838$01239763 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20241115$gRICA 856 4 $uhttps://doi.org/10.1007/978-3-658-37616-1$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 $aVAN00276141 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08DLOAD e-Book 8569 $e08eMF8569 20240604 996 $aReinforcement Learning with Hybrid Quantum Approximation in the NISQ Context$92876327 997 $aUNICAMPANIA