AI has humbled human chess masters. Now it’s helping them take the game to the next level.

What’s new: DeepMind and retired chess champion Vladimir Kramnik trained AlphaZero, a reinforcement learning model that bested human experts in chess, Go, and Shogi, to play-test changes in the rules. Kramnik and others have observed that strategies learned from computers dominate human players’ current approaches. The collaboration aims to infuse the game with new energy.

How it works: AlphaZero is the successor to AlphaGo, the model that famously beat the Go world champion in 2016. The team taught the model nine novel variations of the rules to see how the changes affected gameplay.

  • Five of the variants altered the ways pawns can move. Two restricted defensive strategies. One allowed players to capture their own pieces, and one awarded victory if a player forced the game into a stalemate, or draw.
  • AlphaZero played each variant against itself 10,000 times taking one second per move, then another 1,000 taking one minute per move. The team used the outcomes of these games to assess how the differing rules affected the value of each chess piece.
  • Games with longer turn times resulted in more draws, an indication that these variants require deeper strategic thinking.
  • The new rules spawned many intriguing patterns of play. The variant called self-capture, which allows players to take their own pieces, created more opportunities to sacrifice for strategic gains. The change “makes the game more beautiful,” Kramnik told Wired.

Behind the news: The rules of chess have evolved several times in its 1,500-year history, most famously in the 1400s when the queen was given the ability to move multiple squares in any direction.

Why it matters: In addition to shedding light on new possibilities for an ancient game, AlphaZero sped up the process of play-testing new rules. Game designers could adapt this approach to explore how various tweaks affect their own creations.

We’re thinking: AI and humans have a checkered past, but together they’re finding the right moves.


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