use std::collections::HashMap; use crate::position::{Position, WIDTH, HEIGHT, MIN_SCORE}; const COLUMNS_ORDER: [u64; 7] = [3, 2, 4, 1, 5, 0, 6]; type Cache = HashMap; pub struct Solver { pub visited: usize, pub cache: Cache, } const CACHE_SIZE: usize = 1 << 20 + 1; impl Solver { pub fn new() -> Solver { Solver { visited: 0, cache: Cache::with_capacity(CACHE_SIZE), } } pub fn solve(&mut self, p: Position) -> i32 { self.solve_rec(p, -1000, 1000) } // the weak solver only tells if the position is a win/lose/draw // it's faster but less precise pub fn solve_weak(&mut self, p: Position) -> i32 { self.solve_rec(p, -1, 1) } fn solve_rec(&mut self, p: Position, mut alpha: i32, mut beta: i32) -> i32 { self.visited += 1; if p.is_draw() { return 0; } for x in 0..WIDTH { if p.is_valid_play(x) && p.is_winning_play(x) { return (((WIDTH * HEIGHT + 1) as i32) - (p.play_count as i32)) / 2; } } if let Some(max_score) = self.cache.get(&p.key()) { // can't return max_score directly // because the alpha-beta context in the cache may be // different than the current alpha-beta if beta > *max_score { beta = *max_score; if alpha >= beta { return beta; } } } let mut best = alpha; for x in (0..(WIDTH as usize)) .map(|x| COLUMNS_ORDER[x]) .filter(|x| p.is_valid_play(*x)) { // using negamax, variante of minimax where: // max(player1, player2) == -min(-player1, -player2) let score = -self.solve_rec(p.play(x), -beta, -alpha); if score > best { best = score; // reduce alpha-beta range if found better score if best > alpha { alpha = best; } // impossible alpha-beta range reached (alpha is supposed to be < to beta) if alpha >= beta { return score; } } } self.cache.insert(p.key(), best); return best; } pub fn reset(&mut self) { self.visited = 0; self.cache.clear(); } }