"From Kelly kinyama The engine learns from experience. It writes the moves it plays to the hard disk. In the next game, it uses the same information if it encounters the same position, the same way we use the transposition table. It saves the information permanently on the hard drive, And loads information in memory during play. With the decision tree, it plays more accurately and evaluates the positions more correctly. Notes: -For this method to work, you must always restart the engine for each and every game. -Games should be started from the start position. -Those binary files represent opening variations. We humans give names to the variations. My engine is giving them numbers. So it always knows which file to load in memory. -The engine is constantly updating the files each time it plays."