Solving chess

Solving chess consists of finding an optimal strategy for the game of chess; that is, one by which one of the players (White or Black) can always force a victory, or either can force a draw (see solved game). It is also related to more generally solving chess-like games (i.e. combinatorial games of perfect information) such as Capablanca chess and infinite chess. In a weaker sense, solving chess may refer to proving which one of the three possible outcomes (White wins; Black wins; draw) is the result of two perfect players, without necessarily revealing the optimal strategy itself (see indirect proof). No complete solution for chess in either of the two senses is known, nor is it expected that chess will be solved in the near future (if ever). There is disagreement on whether the current exponential growth of computing power will continue long enough to someday allow for solving it by "brute force", i.e. by checking all possibilities. Progress to date is extremely limited; there are tablebases of perfect endgame play with a small number of pieces (up to seven), and some chess variants have been solved at least weakly. Calculated estimates of game-tree complexity and state-space complexity of chess exist which provide a bird's eye view of the computational effort that might be required to solve the game. Endgame tablebases are computerized databases that contain precalculated exhaustive analyses of positions with small numbers of pieces remaining on the board. Tablebases have solved chess to a limited degree, determining perfect play in a number of endgames, including all non-trivial endgames with no more than seven pieces or pawns (including the two kings). One consequence of developing the seven-piece endgame tablebase is that many interesting theoretical chess endings have been found. The longest seven-piece example is a mate-in-549 position discovered in the Lomonosov tablebase by Guy Haworth, ignoring the 50-move rule.