Serendipity/Gobang-Game
1
1
Fork 0
mirror of https://github.com/LHY0125/Gobang-Game.git synced 2026-06-29 00:45:55 +08:00
Code Issues Packages Projects Releases Wiki Activity

style: cargo fmt 格式化 AI 模块

Browse Source 
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
刘航宇
2026-05-31 15:50:55 +08:00
parent e216ae46dd
commit 8144b16b9d
3 changed files with 96 additions and 45 deletions
Download Patch File Download Diff File Expand all files Collapse all files
core/src/ai/mod.rs
+1 -1
View File
@@ -9,7 +9,7 @@ pub trait AiEngine: Send + Sync {
pub mod evaluate;
pub mod killer;
pub mod opening;
pub mod search;
pub mod trans_table;
pub mod vcf;
pub mod opening;
core/src/ai/opening.rs
+8 -13
View File
@@ -112,7 +112,10 @@ mod tests {
let book = OpeningBook::new();
let board = Board::new(15);
// 开局库在走子后才能匹配，空棋盘作为兜底结果也合理
assert!(book.lookup(board.hash()).is_none(), "空棋盘不应匹配（需至少一手）");
assert!(
book.lookup(board.hash()).is_none(),
"空棋盘不应匹配（需至少一手）"
);
}
#[test]
@@ -126,18 +129,10 @@ mod tests {
let book = OpeningBook::new();
let board = Board::new(15);
// 花月前4手: 黑(7,7) 白(7,8) 黑(6,7) 白(6,6)
let board = board
.place(Position::new(7, 7), Color::Black)
.unwrap();
let board = board
.place(Position::new(7, 8), Color::White)
.unwrap();
let board = board
.place(Position::new(6, 7), Color::Black)
.unwrap();
let board = board
.place(Position::new(6, 6), Color::White)
.unwrap();
let board = board.place(Position::new(7, 7), Color::Black).unwrap();
let board = board.place(Position::new(7, 8), Color::White).unwrap();
let board = board.place(Position::new(6, 7), Color::Black).unwrap();
let board = board.place(Position::new(6, 6), Color::White).unwrap();
assert!(book.lookup(board.hash()).is_some(), "花月前4手应匹配");
}
}
core/src/ai/search.rs
+87 -31
View File
@@ -62,9 +62,8 @@ impl AiEngine for AlphaBetaAi {
break;
}
let (pos, completed) = self.search_depth(
board, color, depth, &mut tt, &mut killer, start, time_limit,
);
let (pos, completed) =
self.search_depth(board, color, depth, &mut tt, &mut killer, start, time_limit);
if let Some(p) = pos {
best_pos = p;
@@ -81,9 +80,14 @@ impl AiEngine for AlphaBetaAi {
impl AlphaBetaAi {
fn search_depth(
&self, board: &Board, color: Color, depth: u32,
tt: &mut TransTable, killer: &mut KillerTable,
start: Instant, time_limit: Duration,
&self,
board: &Board,
color: Color,
depth: u32,
tt: &mut TransTable,
killer: &mut KillerTable,
start: Instant,
time_limit: Duration,
) -> (Option<Position>, bool) {
let candidates = board.get_candidate_moves();
if candidates.is_empty() {
@@ -103,8 +107,11 @@ impl AlphaBetaAi {
.filter(|&&p| !rules::is_forbidden(board, p, color))
.filter_map(|&p| {
board.place(p, color).ok().map(|b| {
if b.check_win(p) { (p, f64::INFINITY) }
else { (p, evaluate_board(&b, color)) }
if b.check_win(p) {
(p, f64::INFINITY)
} else {
(p, evaluate_board(&b, color))
}
})
})
.collect();
@@ -112,9 +119,13 @@ impl AlphaBetaAi {
scored.sort_by(|a, b| {
let a_k = killer_moves.contains(&Some(a.0));
let b_k = killer_moves.contains(&Some(b.0));
if a_k && !b_k { std::cmp::Ordering::Less }
else if !a_k && b_k { std::cmp::Ordering::Greater }
else { b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal) }
if a_k && !b_k {
std::cmp::Ordering::Less
} else if !a_k && b_k {
std::cmp::Ordering::Greater
} else {
b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal)
}
});
for (pos, _) in scored {
@@ -128,8 +139,15 @@ impl AlphaBetaAi {
return (Some(pos), true);
}
let score = -self.negamax(
&new_board, depth - 1, -beta, -alpha, color.opponent(),
tt, killer, start, time_limit,
&new_board,
depth - 1,
-beta,
-alpha,
color.opponent(),
tt,
killer,
start,
time_limit,
);
if score > best_score {
best_score = score;
@@ -145,9 +163,16 @@ impl AlphaBetaAi {
}
fn negamax(
&self, board: &Board, depth: u32, mut alpha: f64, beta: f64, color: Color,
tt: &mut TransTable, killer: &mut KillerTable,
start: Instant, time_limit: Duration,
&self,
board: &Board,
depth: u32,
mut alpha: f64,
beta: f64,
color: Color,
tt: &mut TransTable,
killer: &mut KillerTable,
start: Instant,
time_limit: Duration,
) -> f64 {
if start.elapsed() >= time_limit {
return evaluate_board(board, color);
@@ -160,10 +185,15 @@ impl AlphaBetaAi {
match entry.bound {
BoundType::Exact => return entry.score as f64,
BoundType::LowerBound => alpha = alpha.max(entry.score as f64),
BoundType::UpperBound =>
if (entry.score as f64) <= alpha { return entry.score as f64; },
BoundType::UpperBound => {
if (entry.score as f64) <= alpha {
return entry.score as f64;
}
}
}
if alpha >= beta {
return entry.score as f64;
}
if alpha >= beta { return entry.score as f64; }
}
if depth == 0 {
@@ -182,8 +212,11 @@ impl AlphaBetaAi {
.filter(|&p| !rules::is_forbidden(board, p, color))
.filter_map(|p| {
board.place(p, color).ok().map(|b| {
if b.check_win(p) { (p, f64::INFINITY) }
else { (p, evaluate_board(&b, color)) }
if b.check_win(p) {
(p, f64::INFINITY)
} else {
(p, evaluate_board(&b, color))
}
})
})
.collect();
@@ -191,9 +224,13 @@ impl AlphaBetaAi {
scored.sort_by(|a, b| {
let a_k = killer_moves.contains(&Some(a.0));
let b_k = killer_moves.contains(&Some(b.0));
if a_k && !b_k { std::cmp::Ordering::Less }
else if !a_k && b_k { std::cmp::Ordering::Greater }
else { b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal) }
if a_k && !b_k {
std::cmp::Ordering::Less
} else if !a_k && b_k {
std::cmp::Ordering::Greater
} else {
b.1.partial_cmp(&a.1).unwrap_or(std::cmp::Ordering::Equal)
}
});
let mut max_val = f64::NEG_INFINITY;
@@ -206,12 +243,25 @@ impl AlphaBetaAi {
if let Ok(new_board) = board.place(pos, color) {
if new_board.check_win(pos) {
tt.store(hash, depth as u8, f64::INFINITY as i32, BoundType::Exact, Some(pos));
tt.store(
hash,
depth as u8,
f64::INFINITY as i32,
BoundType::Exact,
Some(pos),
);
return f64::INFINITY;
}
let val = -self.negamax(
&new_board, depth - 1, -beta, -alpha, color.opponent(),
tt, killer, start, time_limit,
&new_board,
depth - 1,
-beta,
-alpha,
color.opponent(),
tt,
killer,
start,
time_limit,
);
if val > max_val {
max_val = val;
@@ -227,9 +277,13 @@ impl AlphaBetaAi {
}
}
let bound = if max_val <= alpha_orig { BoundType::UpperBound }
else if max_val >= beta { BoundType::LowerBound }
else { BoundType::Exact };
let bound = if max_val <= alpha_orig {
BoundType::UpperBound
} else if max_val >= beta {
BoundType::LowerBound
} else {
BoundType::Exact
};
tt.store(hash, depth as u8, max_val as i32, bound, best_move);
max_val
@@ -268,7 +322,9 @@ mod tests {
let mv = ai.best_move(&board, Color::Black).unwrap();
assert!(
(mv.x == 7 && mv.y == 2) || (mv.x == 7 && mv.y == 7),
"AI should win, got ({},{})", mv.x, mv.y
"AI should win, got ({},{})",
mv.x,
mv.y
);
}
}