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1 Ergebnisse
1
Safety-informed mutations for evolutionary deep reinforceme..:
, In:
Proceedings of the Genetic and Evolutionary Computation Conference Companion
,
Marchesini, Enrico
;
Amato, Christopher
- p. 1966-1970 , 2022
Link:
https://dl.acm.org/doi/10.1145/3520304.3533980
RT T1 <cTitle>Proceedings of the Genetic and Evolutionary Computation Conference Companion</cTitle>: T1 <Title>Safety-informed mutations for evolutionary deep reinforcement learning</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3533980&Exemplar=1&LAN=DE A1 Marchesini, Enrico A1 Amato, Christopher PB ACM YR 2022 K1 deep K1 evolutionary algorithms K1 mutations K1 reinforcement learning K1 robotics K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Bio-inspired approaches K1 Evolutionary robotics K1 Learning paradigms K1 Reinforcement learning SP 1966 OP 1970 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3520304.3533980 DO https://dl.acm.org/doi/10.1145/3520304.3533980 SF ELIB - SuUB Bremen
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