Python/backtracking/minimax.py
Christian Clauss cecf43d648
Pyupgrade to Python 3.9 (#4718)
* Pyupgrade to Python 3.9

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Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
2021-09-07 13:37:03 +02:00

71 lines
1.8 KiB
Python

"""
Minimax helps to achieve maximum score in a game by checking all possible moves
depth is current depth in game tree.
nodeIndex is index of current node in scores[].
if move is of maximizer return true else false
leaves of game tree is stored in scores[]
height is maximum height of Game tree
"""
from __future__ import annotations
import math
def minimax(
depth: int, node_index: int, is_max: bool, scores: list[int], height: float
) -> int:
"""
>>> import math
>>> scores = [90, 23, 6, 33, 21, 65, 123, 34423]
>>> height = math.log(len(scores), 2)
>>> minimax(0, 0, True, scores, height)
65
>>> minimax(-1, 0, True, scores, height)
Traceback (most recent call last):
...
ValueError: Depth cannot be less than 0
>>> minimax(0, 0, True, [], 2)
Traceback (most recent call last):
...
ValueError: Scores cannot be empty
>>> scores = [3, 5, 2, 9, 12, 5, 23, 23]
>>> height = math.log(len(scores), 2)
>>> minimax(0, 0, True, scores, height)
12
"""
if depth < 0:
raise ValueError("Depth cannot be less than 0")
if len(scores) == 0:
raise ValueError("Scores cannot be empty")
if depth == height:
return scores[node_index]
if is_max:
return max(
minimax(depth + 1, node_index * 2, False, scores, height),
minimax(depth + 1, node_index * 2 + 1, False, scores, height),
)
return min(
minimax(depth + 1, node_index * 2, True, scores, height),
minimax(depth + 1, node_index * 2 + 1, True, scores, height),
)
def main() -> None:
scores = [90, 23, 6, 33, 21, 65, 123, 34423]
height = math.log(len(scores), 2)
print("Optimal value : ", end="")
print(minimax(0, 0, True, scores, height))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()