ClassicAra
v.0.9.9
Features
First experimental XiangqiAra release.
Move generation back-end and Xiangqi ruleset is based on Fairy-Stockfish.
Uses supervised neural network trained on 10k human Xiangqi games.
Please refer to the thesis Evaluation of Monte-Carlo Tree Search for Xiangqi by Maximilian Langer, pdf for more information.
UCI_Chess_960 support as introduced in https://github.com/QueensGambit/CrazyAra/releases/tag/0.9.8. (However, no official 960 network yet.)
TensorRT API Update #164
Major bug fixes
Handle flooding of UCI-commands (#167)
CrazyAra Going To Infinite Analysis Mode On 1 Position (Can't Be Stopped) In Liground After Making Two Moves On The Board (#81)
Avoid repeating positions in Xiangqi (closes #101) #166
TCEC
This version has been submitted to the TCEC Season 22.
ClassicAra 0.9.9 uses the wdlp-rise3.3-input3.0 model which was trained on the Kingbase2019lite data set as for release 0.9.5.
The engine.json configuration file and update.sh shell script can be used to replicate the testing environment on a multi-GPU Linux operating system.
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