Pythonで学ぶ探索とゲームAI：A*とミニマックス

import heapq

# A* finds the cheapest path using cost so far + a guess of the cost left.
grid = ["S..#",
        ".#..",
        "...G"]
start, goal = (0, 0), (2, 3)
guess = lambda r, c: abs(r - goal[0]) + abs(c - goal[1])   # Manhattan distance

frontier = [(guess(*start), 0, start, [start])]
seen = set()
while frontier:
    _, cost, (r, c), path = heapq.heappop(frontier)
    if (r, c) == goal:
        print("path:", path, "cost:", cost)
        break
    if (r, c) in seen:
        continue
    seen.add((r, c))
    for dr, dc in ((0, 1), (1, 0), (0, -1), (-1, 0)):
        nr, nc = r + dr, c + dc
        if 0 <= nr < 3 and 0 <= nc < 4 and grid[nr][nc] != "#":
            heapq.heappush(frontier, (cost + 1 + guess(nr, nc), cost + 1, (nr, nc), path + [(nr, nc)]))

# Minimax: the maximizer assumes the opponent always picks the worst for it.
def minimax(node, maximizing):
    if isinstance(node, int):
        return node
    values = [minimax(child, not maximizing) for child in node]
    return max(values) if maximizing else min(values)

tree = [[3, 5], [2, 9], [0, 7]]   # our move, then the opponent's reply
print("best guaranteed score:", minimax(tree, True))