/* This file is part of chess_inator. chess_inator is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version. chess_inator is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with chess_inator. If not, see https://www.gnu.org/licenses/. Copyright © 2024 dogeystamp */ //! Game-tree search. use crate::eval::{Eval, EvalInt}; use crate::movegen::{Move, MoveGen, ToUCIAlgebraic}; use crate::Board; use std::cmp::max; // min can't be represented as positive const EVAL_WORST: EvalInt = -(EvalInt::MAX); const EVAL_BEST: EvalInt = EvalInt::MAX; #[cfg(test)] mod test_eval_int { use super::*; #[test] fn test_eval_worst_best_symm() { // int limits will bite you if you don't test this assert_eq!(EVAL_WORST, -EVAL_BEST); assert_eq!(-EVAL_WORST, EVAL_BEST); } } /// Eval in the context of search. #[derive(PartialEq, Eq, Clone, Copy)] enum SearchEval { /// Mate in |n| - 1 half moves, negative for own mate. Checkmate(i8), /// Centipawn score. Centipawns(EvalInt), } impl SearchEval { /// Flip side, and increment the "mate in n" counter. fn increment(self) -> Self { match self { SearchEval::Checkmate(n) => { debug_assert_ne!(n, 0); if n < 0 { Self::Checkmate(-(n - 1)) } else { Self::Checkmate(-(n + 1)) } } SearchEval::Centipawns(eval) => Self::Centipawns(-eval), } } } impl From for EvalInt { fn from(value: SearchEval) -> Self { match value { SearchEval::Checkmate(n) => { debug_assert_ne!(n, 0); if n < 0 { EVAL_WORST + EvalInt::from(n) } else { EVAL_BEST - EvalInt::from(n) } } SearchEval::Centipawns(eval) => eval, } } } impl Ord for SearchEval { fn cmp(&self, other: &Self) -> std::cmp::Ordering { let e1 = EvalInt::from(*self); let e2 = EvalInt::from(*other); e1.cmp(&e2) } } impl PartialOrd for SearchEval { fn partial_cmp(&self, other: &Self) -> Option { Some(self.cmp(other)) } } /// Search the game tree to find the absolute (positive good) move and corresponding eval for the /// current player. /// /// # Arguments /// /// * board: board position to analyze. /// * depth: how deep to analyze the game tree. /// * alpha: best score (absolute, from current player perspective) guaranteed for current player. /// * beta: best score (absolute, from current player perspective) guaranteed for other player. /// /// # Returns /// /// The best move, and its corresponding absolute eval for the current player. fn minmax( board: &mut Board, depth: usize, alpha: Option, beta: Option, ) -> (Option, SearchEval) { // default to worst, then gradually improve let mut alpha = alpha.unwrap_or(EVAL_WORST); // our best is their worst let beta = beta.unwrap_or(EVAL_BEST); if depth == 0 { let eval = board.eval(); match board.turn { crate::Color::White => return (None, SearchEval::Centipawns(eval)), crate::Color::Black => return (None, SearchEval::Centipawns(-eval)), } } let mvs: Vec<_> = board.gen_moves().into_iter().collect(); let mut abs_best = SearchEval::Centipawns(EVAL_WORST); let mut best_move: Option = None; if mvs.is_empty() { if board.is_check(board.turn) { return (None, SearchEval::Checkmate(-1)); } else { // stalemate return (None, SearchEval::Centipawns(0)); } } for mv in mvs { let anti_mv = mv.make(board); let (_best_continuation, score) = minmax(board, depth - 1, Some(-beta), Some(-alpha)); let abs_score = score.increment(); if abs_score >= abs_best { abs_best = abs_score; best_move = Some(mv); } alpha = max(alpha, abs_best.into()); anti_mv.unmake(board); if alpha >= beta { // alpha-beta prune. // // Beta represents the best eval that the other player can get in sibling branches // (different moves in the parent node). Alpha >= beta means the eval here is _worse_ // for the other player, so they will never make the move that leads into this branch. // Therefore, we stop evaluating this branch at all. break; } } (best_move, abs_best) } /// Find the best move. pub fn best_move(board: &mut Board) -> Option { let (mv, eval) = minmax(board, 5, None, None); match eval { SearchEval::Checkmate(n) => println!("info score mate {}", n / 2), SearchEval::Centipawns(eval) => println!("info score cp {eval}"), } mv }