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It's unclear to me how MuZero was able to use less compute to achieve AlphaZero level performance on Go?
by chenzikuy 7y ago
It's unclear to me how MuZero was able to use less compute to achieve AlphaZero level performance on Go?
- smithmayowa 7y ago"They trained the system for five hypothetical steps and a million mini-batches (i.e., small batches of training data) of size 2,048 in board games and size 1,024 in Atari, which amounted to 800 simulations per move for each search in Go, chess, and shogi and 50 simulations for each search in Atari" Because of this I am presuming.
- gok 7y agoFrom the preprint [1]: > In Go, MuZero slightly exceeded the performance of AlphaZero, despite using less computation per node in the search tree (16 residual blocks per evaluation in MuZero compared to 20 blocks in AlphaZero). This suggests that MuZero may be caching its computation in the search tree and using each additional application of the dynamics model to gain a deeper understanding of the position. It also strikes me as possible that just not giving the system the rules to start with might have allowed it to explore more efficient strategies. [1] https://arxiv.org/pdf/1911.08265.pdf https://arxiv.org/pdf/1911.08265.pdf
- deleted 7y ago[deleted]