Public/Chess_Probabilistic_Programming
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

integrated MctsEngine into lichess bot

Browse Source
This commit is contained in:
Lukas Kuess
2024-01-27 22:22:27 +01:00
parent c69b542653
commit 5527c4e4c3
5 changed files with 748 additions and 1166 deletions
Download Patch File Download Diff File Expand all files Collapse all files

45
lichess_bot/lib/strategies.py
View File

@@ -12,7 +12,7 @@ from lib.engine_wrapper import MinimalEngine, MOVE
from typing import Any
import logging
from engines import engine
from chesspp.engine import ClassicMctsEngine
# Use this logger variable to print messages to the console or log files.
# logger.info("message") will always print "message" to the console or log file.
@@ -63,7 +63,8 @@ class ComboEngine(ExampleEngine):
This engine demonstrates how one can use `time_limit`, `draw_offered`, and `root_moves`.
"""
def search(self, board: chess.Board, time_limit: Limit, ponder: bool, draw_offered: bool, root_moves: MOVE) -> PlayResult:
def search(self, board: chess.Board, time_limit: Limit, ponder: bool, draw_offered: bool,
root_moves: MOVE) -> PlayResult:
"""
Choose a move using multiple different methods.
@@ -96,20 +97,30 @@ class ComboEngine(ExampleEngine):
return PlayResult(move, None, draw_offered=draw_offered)
class ProbStockfish(MinimalEngine):
# class ProbStockfish(MinimalEngine):
# def search(self, board: chess.Board, time_limit: chess.engine.Limit, ponder: bool, draw_offered: bool,
# root_moves: MOVE) -> chess.engine.PlayResult:
# moves = {}
# untried_moves = list(board.legal_moves)
# for move in untried_moves:
# mean, std = engine.simulate_stockfish_prob(board.copy(), move, 10, 2)
# moves[move] = (mean, std)
# if mean == 100_000 and std == 0:
# return chess.engine.PlayResult(move, None)
#
# return self.get_best_move(moves)
#
# def get_best_move(self, moves: dict) -> chess.engine.PlayResult:
# best_avg = max(moves.items(), key=lambda m: m[1][0])
# next_move = best_avg[0]
# return chess.engine.PlayResult(next_move, None)
class MctsEngine(MinimalEngine):
def search(self, board: chess.Board, time_limit: chess.engine.Limit, ponder: bool, draw_offered: bool,
root_moves: MOVE) -> chess.engine.PlayResult:
moves = {}
untried_moves = list(board.legal_moves)
for move in untried_moves:
mean, std = engine.simulate_stockfish_prob(board.copy(), move, 10, 2)
moves[move] = (mean, std)
if mean == 100_000 and std == 0:
return chess.engine.PlayResult(move, None)
return self.get_best_move(moves)
def get_best_move(self, moves: dict) -> chess.engine.PlayResult:
best_avg = max(moves.items(), key=lambda m: m[1][0])
next_move = best_avg[0]
return chess.engine.PlayResult(next_move, None)
my_engine = ClassicMctsEngine(board.turn)
print("Color:", board.turn)
print("engine play result: ", my_engine.play(board.copy()))
print("Engine name", my_engine)
return my_engine.play(board.copy())