Details
| Originalsprache | Englisch |
|---|---|
| Veröffentlichungsnummer (amtliches Aktenzeichen) | US2022027743 |
| IPC | G06N 3/ 12 A I |
| Prioritätsdatum | 23 Juli 2020 |
| Publikationsstatus | Veröffentlicht - 27 Jan. 2022 |
Abstract
A method for learning a strategy, which optimally adapts at least one parameter of an evolutionary algorithm. The method includes the following steps: initializing the strategy, which ascertains a parameterization of the parameter as a function of pieces of state information; learning the strategy with the aid of reinforcement learning, it being learned from interactions of the CMA-ES algorithm with a parameterization, determined with the aid of the strategy as a function of the pieces of state information, with the problem instance and with a reward signal, which parameterization is optimal for possible pieces of state information.
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Patent Nr.: US2022027743. Jan. 27, 2022.
Publikation: Schutzrecht/Patent › Patent
}
TY - PAT
T1 - METHOD AND DEVICE FOR LEARNING A STRATEGY AND FOR IMPLEMENTING THE STRATEGY
AU - Adriaenssen, Steven
AU - Biedenkapp, Andre
AU - Hutter, Frank
AU - Shala, Gresa
AU - Lindauer, Marius
AU - Awad, Noor
PY - 2022/1/27
Y1 - 2022/1/27
N2 - A method for learning a strategy, which optimally adapts at least one parameter of an evolutionary algorithm. The method includes the following steps: initializing the strategy, which ascertains a parameterization of the parameter as a function of pieces of state information; learning the strategy with the aid of reinforcement learning, it being learned from interactions of the CMA-ES algorithm with a parameterization, determined with the aid of the strategy as a function of the pieces of state information, with the problem instance and with a reward signal, which parameterization is optimal for possible pieces of state information.
AB - A method for learning a strategy, which optimally adapts at least one parameter of an evolutionary algorithm. The method includes the following steps: initializing the strategy, which ascertains a parameterization of the parameter as a function of pieces of state information; learning the strategy with the aid of reinforcement learning, it being learned from interactions of the CMA-ES algorithm with a parameterization, determined with the aid of the strategy as a function of the pieces of state information, with the problem instance and with a reward signal, which parameterization is optimal for possible pieces of state information.
M3 - Patent
M1 - US2022027743
ER -