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In simple games, we just write a Minimax DP or find the Grundy values (`mex`) to get an **AC**. Bugs aside, have you ever wondered: **does optimal play actually exist in Chess?** If two players with infinite rating play against each other, what is the guaranteed outcome?↵
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In 1913, Ernst Zermelo proved that in any finite, two-player, zero-sum game of perfect information (no dice, no hidden cards), an optimal strategy **must** exist.
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In 1913, Ernst Zermelo proved that in any finite, two-player, zero-sum game of perfect information (no dice, no hidden cards), an optimal strategy **must** exist.↵
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In CP terms, chess is just a massive DAG (thanks to the 50-move and threefold repetition rules preventing infinite loops). Every terminal state has a fixed value: `+1` (White wins), `0` (Draw), or `-1` (Black wins). Using simple Minimax DP:↵
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Since the state graph is finite, the starting board position
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* White has a forced win from move 1.↵
* Black has a forced win from move 1.↵
* Optimal play from both sides **always** leads to a draw.↵
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Why don't we just run a DFS with memoization from
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* **Number of legal positions (States):**
* **Game tree complexity (Variations):**
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For comparison, there are only about
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Since top-down DFS from the start is impossible, computer scientists used **bottom-up DP** (retrograde analysis) starting from checkmates.
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Today, chess is **100% solved for any position with 7 or fewer pieces** (Syzygy Endgame Tablebases). This precomputed DP array takes about **140 Terabytes** of storage. The moment only 7 pieces remain on the board, engines don't calculate anymore—they just do an
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*(Note: Engines like Stockfish and AlphaZero do NOT play optimal chess from move 1. They use Alpha-Beta pruning + neural network heuristics to guess the `dp` value of states at depth 40–50).*↵
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While
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If Alice and Bob play chess optimally, the output is almost certainly **
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What do you think? Will quantum computers ever help us solve 8-piece or 9-piece tablebases, or is chess forever safe from being fully solved?



