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[+] A2 P2.2 (c,d)

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wuliaozhiji
2022-02-19 15:14:52 -05:00
parent fd17a33386
commit a7a755da83
1 changed files with 21 additions and 5 deletions
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assignments/A2/a2_game_tree.py
+21 -5
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@@ -91,6 +91,7 @@ class GameTree:
def add_subtree(self, subtree: GameTree) -> None:
"""Add a subtree to this game tree."""
self._subtrees.append(subtree)
self._update_white_win_probability()
def __str__(self) -> str:
"""Return a string representation of this tree.
@@ -118,7 +119,7 @@ class GameTree:
############################################################################
# Part 1: Loading and "Replaying" Minichess games
############################################################################
def insert_move_sequence(self, moves: list[str]) -> None:
def insert_move_sequence(self, moves: list[str], white_win_probability: float = 0.0) -> None:
"""Insert the given sequence of moves into this tree.
The inserted moves form a chain of descendants, where:
@@ -166,9 +167,10 @@ class GameTree:
>>> sub3.get_subtrees()
[]
"""
self._insert_move_sequence_helper(moves, 0)
self._insert_move_sequence_helper(moves, 0, white_win_probability)
def _insert_move_sequence_helper(self, moves: list[str], index: int) -> None:
def _insert_move_sequence_helper(self, moves: list[str], index: int,
white_win_probability: float) -> None:
# All moves inserted, finish
if index == len(moves):
return
@@ -177,11 +179,11 @@ class GameTree:
# Create subtree if not exist
if not sub:
sub = GameTree(moves[index], not self.is_white_move)
sub = GameTree(moves[index], not self.is_white_move, white_win_probability)
self.add_subtree(sub)
# Insert move
sub._insert_move_sequence_helper(moves, index + 1)
sub._insert_move_sequence_helper(moves, index + 1, white_win_probability)
############################################################################
# Part 2: Complete Game Trees and Win Probabilities
@@ -201,6 +203,20 @@ class GameTree:
- if self is not a leaf and self.is_white_move is False, the white win probability
is equal to the AVERAGE of the white win probabilities of its subtrees
"""
# if self is a leaf, don't change the white win probability
if not self._subtrees:
return
# if self is not a leaf and self.is_white_move is True, the white win probability
# is equal to the MAXIMUM of the white win probabilities of its subtrees
if self.is_white_move:
self.white_win_probability = max(s.white_win_probability for s in self._subtrees)
# if self is not a leaf and self.is_white_move is False, the white win probability
# is equal to the AVERAGE of the white win probabilities of its subtrees
else:
self.white_win_probability = sum(s.white_win_probability for s in self._subtrees) /\
len(self._subtrees)
if __name__ == '__main__':