Please set the Pesrsisted learning to standard for playing on server or your own analysis.
WIth default Off the exp will be ovewritten always.
Only a small hint
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Persisted learning
Default is Off: no learning algorithm. The other values are "Standard" and "Self", this last to activate the Q-learning, optimized for self play. Some GUIs don't write the experience file in some game's modes because the uci protocol is differently implemented
The persisted learning is based on a collection of one or more positions stored with the following format (similar to in memory Stockfish Transposition Table):
best move
board signature (hash key)
best move depth
best move score
best move performance , a new parameter you can calculate with any learning application supporting this specification. An example is the private one, kernel of SaaS part of Alpha-Chess AI portal. The idea is to calculate it based on pattern recognition concept. In the portal, you can also exploit the reports of another NLG (virtual trainer) application and buy the products in the digishop based on all this. This open-source part has the performance default. So, it doesn't use it. Clearly, even if already strong, this private learning algorithm is a lot stronger as demostrate here: Graphical result
This file is loaded in an hashtable at the engine load and updated each time the engine receive quit or stop uci command. When BrainLearn starts a new game or when we have max 8 pieces on the chessboard, the learning is activated and the hash table updated each time the engine has a best score at a depth >= 4 PLIES, according to Stockfish aspiration window.
At the engine loading, there is an automatic merge to experience.bin files, if we put the other ones, based on the following convention: