Leela Chess Zero (Lc0) is a neural network based chess engine.
Lc0, like most other chess engines, implements the Universal Chess Interface (UCI) protocol and requires a chess GUI.
This is free and open source software.
To have a trained network, you need to think about three aspects:
- Network structure.
- Training data.
- Training procedure.
Network structure defines:
- Supported features (e.g., whether it is able to predict probability of Win/Draw/Loss or only expected outcome).
- Network capacity, how much it is able to “know” in the end.
- Generally, larger networks have better capacity, but slower to use and train.
- How easy it learns (often hard to predict, but some structures learn better than others).
Network needs millions of example chess games to learn. The games have to be both very high-level for a network to learn strong moves, and contain weaker moves so that the network learns to avoid them and know how to exploit them.
When it comes to training a neural network, there is a vast space of methods and parameters to pick from, including choosing an optimizer and selecting a learning rate schedule.
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