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IBM Research issues Ultimate Ultimate Tic-Tac-Toe challenge

IBM Research has issued its October 2026 Ponder This challenge, tasking math and computer science enthusiasts with solving a highly constrained variant of Ultimate Tic-Tac-Toe.

IBM Research AI14 hrs agoCulture
Image: IBM Research AI

IBM Research has published its October 2026 Ponder This challenge, inviting participants to solve a complex puzzle based on Ultimate Tic-Tac-Toe. The standard game is played on a 9 by 9 board, which is divided into nine 3 by 3 small boards. Players X and O take turns, starting with X. The core mechanic dictates that a move in cell (x, y) forces the opponent to make their next move in the small board located at (x mod 3, y mod 3). For instance, playing in cell (4, 6) forces the next move into the middle-left small board at (1, 0).

When a player wins a small board, it becomes locked and takes on that player's global value. If a small board is completely filled without a winner, it is locked with no global value. If a player is directed to a locked board, they may play in any free cell on any unlocked board. The overall game is won when the global values of the small boards align to form a traditional 3 by 3 Tic-Tac-Toe win. Cells are numbered from 0 to 80, starting from the top-left and moving row by row.

The October 2026 challenge requires finding an 'Ultimate Ultimate Tic-Tac-Toe Game.' This specific game must last exactly 81 moves to fill the entire board. Crucially, the final 9 moves of the game must each win one of the small boards, meaning no small board can be won earlier, and there can be no ties. Players are allowed to cooperate and make seemingly irrational moves to achieve this sequence. IBM also offers a bonus star for solving a larger 5 by 5 variation, which features 25 small boards of 5 by 5 cells each, with moves numbered from 0 to 624.

For computer science practitioners, solving this challenge requires designing efficient search algorithms, constraint satisfaction models, or heuristic-driven solvers to navigate a massive state space. The strict constraints on the final nine moves significantly narrow the valid solution paths, making it an excellent benchmark for testing backtracking and optimization techniques.

This is our own summary of reporting by IBM Research AI

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