AI algorithm of Surakarta chess based on chessboard key position assessment value

An AI algorithm of Surakarta chess based on a chessboard key position assessment value comprises multi-thread parallel searching method (searching in short) based on multiple optimization methods and a composition evaluation method (value assessment in short) based on key position value assessment. The AI algorithm is characterized in that at a searching aspect, historical elicitation, PVS ultrasmall-window searching, Zobrist Hash and multi-thread optimization method are successively added into a strategy 101, a strategy 102, a strategy 103, a strategy 104 and a strategy 105 for improving searching efficiency in Alphabeta searching, namely improving searching depth as possible through combining with a plurality of optimization methods, and realizing matching of the optimization methods, thereby greatly improving efficiency; at the assessment value aspect, adopting different assessment values at different periods; and meanwhile, utilizing different corresponding parameters for different roles at an offensive position and a defensive position, thereby realizing different purposes of attacking and defending. After all, through consideration at multiple aspects, higher assessment accuracy is realized and higher chess playing level are realized.