Difference between revisions of "KataHex"
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== Pre-trained networks == | == Pre-trained networks == | ||
| − | HZY initially trained the neural network model on two NVIDIA GeForce RTX 2080 Ti GPUs for about 20 days. They then up-trained the network on 19x19 for one day, and on 27x27 for an additional day. [https://zhuanlan-zhihu-com.translate.goog/p/476464087?_x_tr_sl=auto&_x_tr_tl=en According to HZY], the up-trained 19x19 network is relatively reliable, but the 27x27-network is not. | + | HZY initially trained the neural network model on two NVIDIA GeForce RTX 2080 Ti GPUs for about 20 days on 13x13. They then up-trained the network on 19x19 for one day, and on 27x27 for an additional day. [https://zhuanlan-zhihu-com.translate.goog/p/476464087?_x_tr_sl=auto&_x_tr_tl=en According to HZY], the up-trained 19x19 network is relatively reliable, but the 27x27-network is not. |
Each pre-trained neural network is able to play Hex at the size it was trained on, or any smaller size. Thus, the 19x19 network model can also be used to play 11x11 or 13x13. | Each pre-trained neural network is able to play Hex at the size it was trained on, or any smaller size. Thus, the 19x19 network model can also be used to play 11x11 or 13x13. | ||
Latest revision as of 23:49, 16 January 2024
KataHex is a free and open-source computer Hex program, capable of defeating top-level human players. It implements Monte Carlo tree search with a convolutional neural network providing position evaluation and policy guidance.
History and versions
KataHex is based on KataGo, a computer Go program developed by David Wu that was first released on 27 February 2019. It was adapted for Hex by "HZY" between February 2020 and May 2022. While initially unnamed, the Hex-adaptation of KataGo quickly became known as "KataHex" among Hex players.
The HZY implementation of KataHex speaks a non-standard dialect of GTP and can only interact with a specially modified version of the Go GUI known as LizzieYzy. A further adaptation of KataHex that is capable of interfacing with Hexgui was made by Selinger.
Pre-trained networks
HZY initially trained the neural network model on two NVIDIA GeForce RTX 2080 Ti GPUs for about 20 days on 13x13. They then up-trained the network on 19x19 for one day, and on 27x27 for an additional day. According to HZY, the up-trained 19x19 network is relatively reliable, but the 27x27-network is not.
Each pre-trained neural network is able to play Hex at the size it was trained on, or any smaller size. Thus, the 19x19 network model can also be used to play 11x11 or 13x13.
"KataHex" refers generally to the KataHex program, but often more specifically to the pre-trained 19x19 neural network made by HZY.
Limitations
Since KataHex was only trained on self-play, it does not always do well when asked to play from an arbitrary starting position. It seems to be particularly thrown off if the starting position does not have the same number of black and white stones.
Links
Program:
- David Wu's original KataGo: <https://github.com/lightvector/KataGo>
- HZY's KataHex: <https://github.com/hzyhhzy/KataGo/tree/Hex2022>
- Selinger's moficiations: <https://github.com/selinger/katahex>
Pre-trained network models:
- HZY's pre-trained 19x19 network: katahex_model_20220618.bin.gz
GUIs:
- HZY's KataHex works with this modified LizzieYzy GUI: KataHex_LizzieYZY_20220313.zip.
- Selinger's KataHex works with HexGUI: <https://github.com/selinger/hexgui>
Analysis:
- HZY's analysis of win-rates for opening moves: Chinese English
- Strategic advice from KataHex
