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feat(core): AI Alpha-Beta 搜索 — Negamax + 剪枝 + 启发式排序
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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//! AI 搜索模块 — 占位符, 待实现 Alpha-Beta 搜索
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//! TODO: 在 Task 6 中实现完整搜索逻辑
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use crate::ai::evaluate::evaluate_board;
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use crate::ai::AiEngine;
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use crate::board::Board;
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use crate::types::{Color, Position};
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/// Alpha-Beta AI 引擎
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pub struct AlphaBetaAi {
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depth: usize,
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}
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impl AlphaBetaAi {
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pub fn new(depth: usize) -> Self {
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Self { depth }
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}
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}
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impl AiEngine for AlphaBetaAi {
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fn best_move(&self, board: &Board, color: Color) -> Option<Position> {
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let candidates = board.get_candidate_moves();
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if candidates.is_empty() {
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return None;
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}
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let mut best_pos = None;
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let mut best_score = f64::NEG_INFINITY;
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for &pos in &candidates {
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if let Ok(new_board) = board.place(pos, color) {
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if new_board.check_win(pos) {
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return Some(pos);
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}
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let score = -self.negamax(
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&new_board,
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self.depth - 1,
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f64::NEG_INFINITY,
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f64::INFINITY,
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color.opponent(),
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);
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if score > best_score {
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best_score = score;
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best_pos = Some(pos);
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}
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}
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}
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best_pos
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}
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}
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impl AlphaBetaAi {
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fn negamax(
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&self,
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board: &Board,
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depth: usize,
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mut alpha: f64,
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beta: f64,
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color: Color,
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) -> f64 {
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if depth == 0 {
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return evaluate_board(board, color);
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}
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let candidates = board.get_candidate_moves();
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if candidates.is_empty() {
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return evaluate_board(board, color);
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}
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// 启发式排序:先评估每步棋,优先搜索高分走法
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let mut scored: Vec<(Position, f64)> = candidates
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.into_iter()
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.filter_map(|pos| {
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board.place(pos, color).ok().map(|b| {
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if b.check_win(pos) {
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(pos, f64::INFINITY)
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} else {
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let s = evaluate_board(&b, color);
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(pos, s)
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}
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})
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})
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.collect();
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scored.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal));
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let mut max_val = f64::NEG_INFINITY;
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for (pos, _) in scored {
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if let Ok(new_board) = board.place(pos, color) {
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if new_board.check_win(pos) {
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return f64::INFINITY;
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}
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let val = -self.negamax(
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&new_board,
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depth - 1,
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-beta,
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-alpha,
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color.opponent(),
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);
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if val > max_val {
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max_val = val;
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}
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if val > alpha {
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alpha = val;
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}
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if alpha >= beta {
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break;
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}
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}
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}
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max_val
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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use crate::ai::AiEngine;
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use crate::board::Board;
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use crate::types::{Color, Position};
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#[test]
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fn test_ai_returns_center_on_empty_board() {
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let board = Board::new(15);
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let ai = AlphaBetaAi::new(1);
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let mv = ai.best_move(&board, Color::Black);
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assert!(mv.is_some());
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let pos = mv.unwrap();
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assert!(pos.x >= 6 && pos.x <= 8);
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assert!(pos.y >= 6 && pos.y <= 8);
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}
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#[test]
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fn test_ai_blocks_rush_four() {
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// 白棋活三 (一端被己方黑棋堵住, 只有一端开放)
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let board = Board::new(15);
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let mut board = board;
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board = board.place(Position::new(7, 1), Color::Black).unwrap();
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board = board.place(Position::new(7, 2), Color::White).unwrap();
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board = board.place(Position::new(7, 3), Color::White).unwrap();
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board = board.place(Position::new(7, 4), Color::White).unwrap();
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board = board.place(Position::new(7, 5), Color::White).unwrap();
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let ai = AlphaBetaAi::new(3);
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let mv = ai.best_move(&board, Color::Black).unwrap();
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assert_eq!(
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mv,
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Position::new(7, 6),
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"AI should block rush four at (7,6), got ({},{})",
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mv.x,
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mv.y
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);
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}
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#[test]
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fn test_ai_blocks_four_near_edge() {
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// 白棋冲四 (靠边), 黑棋只需堵住开放端
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let board = Board::new(15);
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let mut board = board;
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board = board.place(Position::new(7, 0), Color::White).unwrap();
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board = board.place(Position::new(7, 1), Color::White).unwrap();
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board = board.place(Position::new(7, 2), Color::White).unwrap();
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board = board.place(Position::new(7, 3), Color::White).unwrap();
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let ai = AlphaBetaAi::new(3);
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let mv = ai.best_move(&board, Color::Black).unwrap();
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assert_eq!(
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mv,
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Position::new(7, 4),
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"AI should block four at (7,4), got ({},{})",
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mv.x,
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mv.y
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);
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}
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#[test]
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fn test_ai_takes_win() {
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// 黑棋连四, (7,2) 和 (7,7) 都是胜着
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let board = Board::new(15);
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let mut board = board;
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board = board.place(Position::new(7, 3), Color::Black).unwrap();
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board = board.place(Position::new(7, 4), Color::Black).unwrap();
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board = board.place(Position::new(7, 5), Color::Black).unwrap();
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board = board.place(Position::new(7, 6), Color::Black).unwrap();
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let ai = AlphaBetaAi::new(3);
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let mv = ai.best_move(&board, Color::Black).unwrap();
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assert!(
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(mv.x == 7 && mv.y == 2) || (mv.x == 7 && mv.y == 7),
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"AI should take winning move, got ({},{})",
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mv.x,
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mv.y
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);
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}
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}
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