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- W3103133775 abstract "Recently a strong poker-playing algorithm called DeepStack was published, which is able to find an approximate Nash equilibrium during gameplay by using heuristic values of future states predicted by deep neural networks. This paper analyzes new ways of encoding the inputs and outputs of DeepStack's deep counterfactual value networks based on traditional abstraction techniques, as well as an unabstracted encoding, which was able to increase the network's accuracy." @default.
- W3103133775 created "2020-11-23" @default.
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- W3103133775 date "2018-01-01" @default.
- W3103133775 modified "2023-10-03" @default.
- W3103133775 title "Analysis and Optimization of Deep Counterfactual Value Networks" @default.
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- W3103133775 doi "https://doi.org/10.1007/978-3-030-00111-7_26" @default.
- W3103133775 hasPublicationYear "2018" @default.
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