A0lite

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A0lite,
a didactic UCI compliant neural network chess engine by Dietrich Kappe, written in Python, released in March 2020 under the permissive MIT License [1] as successor of LeelaLite, already announced in October 2018 [2]. A0lite applies upper confidence bounds to Monte-Carlo trees, and requires the installation of the Bad Gyal PyTorch net evaluator, by default using MeanGirl-8 (32x4) net on CPU [3]. A0lite had its official tournament debut at the Qualification League of TCEC Season 19.

Quotes

Dietrich Kappe explained his motivation for writing A0lite on CCC, Mar 06, 2021 [4] :

1. Teaching other people how simple it is to write a basic mcts/nn engine with a0lite python.
2. Experimenting with new nn architectures and non-RL training approaches.
3. Combining ab/nnue and mcts/nn in a hybrid approach. (Was a0lite julia, renamed Bender)
4. Reach 3300 ccrl


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