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Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data
Deep neural networks have been successfully applied in learning the board games Go, chess, and shogi without prior knowledge by making use of reinforcement learning. Although starting from zero knowledge has been shown to yield impressive results, it is associated with high computationally costs esp...
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| Vydáno v: | Front Artif Intell |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Frontiers Media S.A.
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7861260/ https://ncbi.nlm.nih.gov/pubmed/33733143 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/frai.2020.00024 |
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