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The game-over line is bold green for a win, naming the winning player,
and bold yellow for a draw. The last-turn panel shows a minimax
player's score to 5 significant figures.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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A position coming up for the third time with the same side to move ends
the game as a draw, in the TUI and in training self-play. Players now get
the game's earlier boards in pick_move, and the search scores the first
repetition on its path as a draw, so a side that is ahead avoids one and
a side that is behind seeks one.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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- NeuralPlayer: a MinimaxPlayer that scores positions with a small MLP
(network.rs, hand-written backprop and Adam, no new dependencies)
- train subcommand: self-play with TD(lambda) targets, cut at random
exploration moves so sheep blunders don't bias the net towards tigers
- neural subcommand: play against a trained network
- evaluate now gets the side to move
- Board symmetries; the search cache keys by the canonical board, which
halves the depth-9 bench time with identical moves and scores
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Added benchmarking capabilities
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Now uses ratatui
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What works:
- Minimax search
- With a simple player claude designed
- Manual player
- Move generation
- Board display
What needs improvement:
- Manual player
- Game coordinator
- Draw checking
- Nix setup
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