00902cam0-2200325---450-99000405972040332120140710155522.088-7648-056-0000405972FED01000405972(Aleph)000405972FED0100040597219990604d1987----km-y0itay50------baitaITa-------001ybAmaliala rivincita della femminaMarziano GuglielminettiGenovaCosta & Nolan1987188 p.ill.18 cmRiscontri5Guglielminetti, AmaliaBiografia853.912Guglielminetti,Marziano<1937-2006>151921ITUNINARICAUNIMARCBK990004059720403321853.912 GUG 3Dip.f.m.2167FLFBCFLFBCAmalia137872UNINA01605nam0 22003733i 450 VAN0027614020240806101544.395N978365839179920240521d2022 |0itac50 baengDE|||| |||||Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop SchedulingSchirin BärWiesbadenSpringer Vieweg2022xxii, 148 p.ill.24 cm68-XXComputer science [MSC 2020]VANC019670MF97-XXMathematics education [MSC 2020]VANC023813MFFlexible ManufacturingKW:KJob Shop SchedulingKW:KMachine learningKW:KMulti-Agent SystemKW:KProduction SchedulingKW:KReinforcement LearningKW:KDEWiesbadenVANL000457BärSchirinVANV2288371261730Springer <editore>VANV108073650ITSOL20241115RICAhttps://doi.org/10.1007/978-3-658-39179-9E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICAIT-CE0120VAN08NVAN00276140BIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA08DLOAD e-Book 8568 08eMF8568 20240604 Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling2940556UNICAMPANIA