Pathfinding with Dijkstra

This commit is contained in:
jona605a
2020-08-08 13:23:11 +02:00
parent 73b0a21a48
commit 3b7769599a

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@ -16,6 +16,12 @@ AIScoresHex = {
}
BOARDWIDTH = 11
ALL_POSITIONS = [(i,j) for i in range(11) for j in range(11)]
ALL_SET = set(ALL_POSITIONS)
EMPTY_DIJKSTRA = {}
for position in ALL_POSITIONS:
EMPTY_DIJKSTRA[position] = math.inf # an impossibly high number
HEX_DIRECTIONS = [(0,1),(-1,1),(-1,0),(0,-1),(1,-1),(1,0)]
# Parses command
@ -200,14 +206,48 @@ def placeOnHexBoard(board,player,position):
logThis("Cannot place on existing piece (error code 1532)")
return "Error. You must place on an empty space."
# Checks if someone has won the game and returns the winner
def isHexWon(board):
won = 0
winningPieces = []
# you know... code here
def evaluateBoard(board):
score = {1:0, 2:0}
isWon = False
# Here, I use Dijkstra's algorithm to evaluate the board, as proposed by this article: https://towardsdatascience.com/hex-creating-intelligent-adversaries-part-2-heuristics-dijkstras-algorithm-597e4dcacf93
for player in [1,2]:
logThis("Running Dijkstra for player "+str(player))
Distance = copy.deepcopy(EMPTY_DIJKSTRA)
# Initialize the starting hexes. For the blue player, this is the leftmost column. For the red player, this is the tom row.
for start in (ALL_POSITIONS[::11] if player == 2 else ALL_POSITIONS[:11]):
# An empty hex adds a of distance of 1. A hex of own color add distance 0. Opposite color adds infinite distance.
Distance[start] = 1 if (board[v[0]][v[1]] == 0) else 0 if (board[v[0]][v[1]] == player) else math.inf
visited = set() # Also called sptSet, short for "shortest path tree Set"
while len(ALL_SET.difference(visited)): # While there are any un-visited hexes
# Find the next un-visited hex, that has the lowest distance
remainingHexes = ALL_SET.difference(visited)
A = [Distance[k] for k in remainingHexes] # Find the distance to each un-visited hex
u = list(remainingHexes)[A.index(min(A))] # Chooses the one with the lowest distance
# Find neighbors of the hex u
for di in HEX_DIRECTIONS:
v = (u[0] + di[0] , u[1] + di[1]) # v is a neighbor of u
if v[0] in range(11) and v[1] in range(11) and v not in visited:
new_dist = Distance[u] + (1 if (board[v[0]][v[1]] == 0) else 0 if (board[v[0]][v[1]] == player) else math.inf)
Distance[v] = min(Distance[v], new_dist)
# If at the goal and the distance is still 0, we've won!
if new_dist == 0 and v[player-1] == 10: # if the right coordinate of v is 10, it means we're at the goal
isWon = True
break
if isWon:
score[player] = math.inf # Winner!
score[player%2 +1] = -math.inf # loser!
break
# After a hex has been visited, this is noted
visited.add(u)
logThis("Distance from player {}'s start to {} is {}".format(player,u,Distance[u]))
# When all hexes on the board have been checked:
score = # the minimum distance of the row of the goal
return score, isWon
return won, winningPieces
# Plays as the AI
def hexAI(channel):
@ -257,33 +297,6 @@ def hexAI(channel):
placement = "abcdefghijk"[chosenMove[1]]+str(chosenMove[0]+1)
return placeHex(channel,placement, "Gwendolyn")
# Calculates points for a board
def AICalcHexPoints(board,player):
score = 0
#otherPlayer = player%2+1
## Checks if anyone has won
#won = isHexWon(board)[0]
## Add points if AI wins
#if won == player:
# score += AIScoresHex["win"]
return score
#def evaluateWindow(window,player,otherPlayer):
# if window.count(player) == 4:
# return AIScoresHex["win"]
# elif window.count(player) == 3 and window.count(0) == 1:
# return AIScoresHex["three in a row"]
# elif window.count(player) == 2 and window.count(0) == 2:
# return AIScoresHex["two in a row"]
# elif window.count(otherPlayer) == 4:
# return AIScoresHex["enemy win"]
# else:
# return 0
def minimaxHex(board, depth, player , originalPlayer, alpha, beta, maximizingPlayer):
terminal = ((isHexWon(board)[0] != 0) or (0 not in board[0]))