Reinforcement learning using target neural networks
US11049008B2 · kind B2 · utility
7Cited by
2References
29Claims
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Key dates
| Filing date | Jun 9, 2017 |
| Grant date | Jun 29, 2021 |
| Priority date | — |
| Expiry date | Dec 27, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
We describe a method of reinforcement learning for a subject system having multiple states and actions to move from one state to the next. Training data is generated by operating on the system with a succession of actions and used to train a second neural network. Target values for training the second neural network are derived from a first neural network which is generated by copying weights of the second neural network at intervals.
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