This is a game of chess played by two AI engines each far better at chess than any human on earth. The question I had is what happens when you let these machines battle it out on an infinite chessboard with infinite pieces. Each move calculated and performed on an 8x8 subset that in isolation is a totally legal position with two kings but in the big picture is just a tiny subset of a much bigger game.

Where each checkmate destroys the king and the deserted pieces move on in search of another neighboring victim. Pieces get captured and sacrificed in other words the usual game of chess but on a much bigger board. The play is extended arbitrarily outwards but here we focus on just this subset of about 6,000 squares.

On the bottom is the counter showing the number of kings and checkmate victories. Let me mention some details. The boards are initialized with the middle game position for one of 30,000 famous grandmaster games including Magnus Carlsen, Bobby Fischer, Gasparo, Spassky, Tal, Karpov and so on. The selection of which 8x8 subset to use for computing the next move is made randomly among all the boards that have legal chess positions.

Optimizing the selection process is something that could be formulated as a reinforcement learning problem and would make this meta game of infinite chess very interesting. In fact there are fascinating questions here about the generalizability of AI engines far beyond the scale and the constraints of the game they were trained on.

Chess is just a game but when you start to remove the constraints and increase the scale it becomes something else. Something more like the game of life played on an infinite chess board.