In [1]:
import numpy as np
from random import randint, random, choice
import matplotlib.pyplot as plt
from math import sqrt, log
%matplotlib inline
In [2]:
class Board(object):
def __init__(self, num_players, rewards):
self.n_players = num_players
self.rewards = rewards
self.grid = [[0 for i in range(16)] for j in range(16)]
self.cur_turn = 1
self.baseCamps = {2: [0, 0], 1: [15, 15]}
self.this_turn_visited = []
self.last_moved = [None, None]
self.starting_positions = {}
if self.n_players == 2:
self.starting_positions[1] = [[0, 0], [0, 1], [0, 2], [0, 3], [0, 4], [1, 0], [1, 1], [1, 2], [1, 3], [1, 4], [2, 0], [2, 1], [2, 2], [2, 3], [3, 0], [3, 1], [3, 2], [4, 0], [4, 1]]
self.starting_positions[2] = [[15, 11], [15, 12], [15, 13], [15, 14], [15, 15], [14, 11], [14, 12], [14, 13], [14, 14], [14, 15], [13, 12], [13, 13], [13, 14], [13, 15], [12, 13], [12, 14], [12, 15], [11, 14], [11, 15]]
# if self.cur_turn == 2:
# self.opponentMove()
def printBoard(self):
for r in self.grid:
print(r)
def reset(self):
self.grid = [[0 for i in range(16)] for j in range(16)]
if self.n_players == 2:
for player, lst in self.starting_positions.items():
for x, y in lst:
self.grid[x][y] = player
# def opponentMove(self):
# opponent = Agent(self, 2, [15, 15])
# opponent.move()
# print("NOT COMPLETE")
def checkWin(self, player):
if self.n_players == 2:
win_positions = self.starting_positions[self.n_players - player + 1]
for x, y in win_positions:
if self.grid[x][y] != player:
return False
return True
def inBounds(self, i, j):
if i < 0 or j < 0 or j > 15 or i > 15:
return False
return True
def checkDist(self, x, y, other = None):
if not other:
other = self.baseCamps[self.cur_turn]
baseX, baseY = other
return ((baseY - y)**2 + (baseX-x)**2)**.5
def getLegalComplete(self, i, j, positive = None):
# BFS from i, j
legal = {"moves": [], "jumps": []}
if self.grid[i][j] == 0:
print(i, j, self.grid[i])
print("Why are you trying to move a blank space?")
return legal
else:
visited = [[False for i in range(16)] for j in range(16)]
queue = [[i, j]]
while queue:
x, y = queue.pop(0)
if not visited[x][y]:
if [x, y] != [i, j]:
legal["jumps"].append([x, y])
for k in range(-1, 2):
for l in range(-1, 2):
if self.inBounds(x + 2*k, y + 2*l) and self.grid[x + 2*k][y + 2*l] == 0 and self.grid[x + k][y + l] != 0:
if not visited[x + 2*k][y + 2*l]:
queue.append([x + 2*k, y + 2*l])
visited[x][y] = True
for k in range(-1, 2):
for l in range(-1, 2):
if self.inBounds(i + k, j + l) and self.grid[i + k][j + l] == 0:
legal["moves"].append([i + k, j + l])
return legal
def getLegal(self, i, j, positive = None, jump = False):
legal = {"moves": [], "jumps": []}
if self.grid[i][j] == 0:
print(i, j, self.grid[i])
print("Why are you trying to move a blank space?")
return legal
else:
for k in range(-1, 2):
for l in range(-1, 2):
myDist = self.checkDist(i, j, other = positive)
if self.inBounds(i + 2*k, j + 2*l) and self.grid[i + 2*k][j + 2*l] == 0 \
and self.grid[i + k][j + l] != 0:
newDist = self.checkDist(i + 2*k, j + 2*l, other = positive)
if (myDist > newDist):
legal["jumps"].append([i + 2*k, j + 2*l, newDist])
if not jump:
if self.inBounds(i + k, j + l) and self.grid[i + k][j + l] == 0:
newDist = self.checkDist(i + k, j + l, other = positive)
if (myDist > newDist):
legal["moves"].append([i + k, j + l, newDist])
return legal
def checkLegal(self, player, i, j, k, l):
if self.grid[k][l] != 0 or self.grid[i][j] != player:
# if random() < 0.01:
# print("You can't do that move")
# print "Here's why. Grid at k, l isn't 0?:", k, l, self.grid[k][l], "Or at i, j, isn't player", player, i, j, self.grid[j][j]
return False
else:
legal = self.getLegalComplete(i, j)
# TODO - This currently doesn't work because the getLegal() above needs to be passed a proper
# value for "positive"
# if [k, l] not in [[m[0], m[1]] for m in legal["moves"]] and \
# [k, l] not in [[m[0], m[1]] for m in legal["jumps"]]:
# print("Not legal move")
# print(i, j, k, l, legal)
# return False
return True
def move(self, player, i, j, k, l, pBoard = False):
if self.checkLegal(player, i, j, k, l) == True and self.cur_turn == player:
self.grid[i][j] = 0
self.grid[k][l] = player
# set last moved
self.last_moved = [k, l]
# record in our path
if self.this_turn_visited == []:
self.this_turn_visited.append([i, j])
self.this_turn_visited.append([k, l])
# check if we're able to move again
new_moves = self.getLegal(k, l)
# end turn if we didn't just jump and there are still legal jumps, and we didn't just move one space
if not new_moves["jumps"] or (k - i != 2 and l - j != 2):
self.cur_turn = 3 - self.cur_turn
self.this_turn_visited = []
if pBoard:
self.printBoard()
In [3]:
board = Board(2, 0)
board.reset()
board.printBoard()
board.move(1, 0, 4, 0, 5)
board.printBoard()
print(board.getLegalComplete(2, 2))
In [5]:
class Agent(object):
def __init__(self, board, ID, baseOrigin):
self.ID = ID
self.baseOrigin = baseOrigin
self.board = board
self.pieces = self.board.starting_positions[self.ID]
self.overrideDist = False
def updateBoard(self, board):
self.board = board
def findPieces(self, board):
pieces = []
for i in range(len(board.grid)):
for j in range(len(board.grid[i])):
if board.grid[i][j] == self.ID:
pieces.append([i, j])
return pieces
def distToOther(self, piece, other = None):
if not other:
other = self.baseOrigin
baseX, baseY = other
pieceX, pieceY = piece
return ((baseY - pieceY)**2 + (baseX-pieceX)**2)**.5
def bestPiece(self, distPieces = None, mp = None):
if not distPieces:
distPieces = sorted([[self.distToOther(piece), piece] for piece in self.pieces])
for piece in distPieces:
i, j = piece[1]
legals = self.board.getLegal(i, j, positive = mp)
if legals["jumps"] or legals["moves"]:
return [(i, j), legals]
return [False, False]
def bestMove(self, mustJump = None, eps = .2):
if mustJump:
piece = mustJump
legals = self.board.getLegal(piece[0], piece[1], jump = True)
elif self.overrideDist:
# Find the pieces that are not in the right positions
s = self.board.starting_positions[self.board.n_players-self.ID+1]
missedPieces = [x for x in self.pieces if x not in s]
# Find the first missing position
missedPos = [x for x in s if x not in self.pieces]
if not missedPos:
print "Erroneous"
return [False, False]
mp = missedPos[0]
# Calculate distances and find best move using those
distPieces = sorted([[self.distToOther(piece, mp), piece] for piece in missedPieces], reverse=True)
piece, legals = self.bestPiece(distPieces = distPieces, mp = mp)
else:
piece, legals = self.bestPiece()
if not piece or not legals:
return [False, False]
if legals["jumps"]:
distJumps = sorted(legals["jumps"], reverse=True, key=lambda i: i[2])
if random() < eps:
target = choice(distJumps)
else:
target = distJumps[0]
return [(piece[0], piece[1], target[0], target[1]), True]
elif legals["moves"] and not mustJump:
distMoves = sorted(legals["moves"], reverse=True, key=lambda i: i[2])
if random() < eps:
target = choice(distMoves)
else:
target = distMoves[0]
return [(piece[0], piece[1], target[0], target[1]), False]
else:
return [False, False]
def move(self):
move, jumped = self.bestMove()
# If no move available, clearly we are in a deadlock
if not move:
self.overrideDist = True
move, jumped = self.bestMove()
if not move:
print self.ID, self.overrideDist
return False
# Make move on board and record pieces
i, j, k, l = move
self.board.move(self.ID, i, j, k, l)
self.pieces = self.findPieces(self.board)
# Continue jumping if already done so
while jumped:
move, jumped = self.bestMove(mustJump = [k, l])
if move:
i, j, k, l = move
self.board.move(self.ID, i, j, k, l)
self.pieces = self.findPieces(self.board)
# Return the final move made
self.board.cur_turn = 3 - self.board.cur_turn
return move
In [6]:
board = Board(2, 0)
board.reset()
print(board.cur_turn)
opponent = Agent(board, 2, [15, 15])
player = Agent(board, 1, [0, 0])
for i in range(160):
opponent.move()
player.move()
board.printBoard()
print(board.cur_turn)
In [72]:
moveRew = -1
winRew = 100
def PlayGame(nplayers = 2):
brd = Board(nplayers, 0)
brd.reset()
opponent = Agent(brd, 2, [15, 15])
player = Agent(brd, 1, [0, 0])
players = [opponent, player]
# # for i in range(250):
# # opponent.move()
# # player.move()
rewards = {1: [], 2: []}
m, m1 = 0, 0
c = 0
while True:
for p in players:
# Check if game is ended
if brd.checkWin(p.ID):
rewards[p.ID].append(winRew)
return p, rewards
m = p.move()
rewards[p.ID].append(moveRew)
brd = p.board
c+=1
In [73]:
lol = PlayGame()
In [74]:
plays = 100
In [75]:
wins = {1: 0, 2: 0}
rews = {1: [], 2: []}
for i in range(plays):
p, r = PlayGame()
wins[p.ID] += 1
rews[1].append(np.sum(r[1]))
rews[2].append(np.sum(r[2]))
cumrews = {1: np.cumsum(rews[1]), 2: np.cumsum(rews[2])}
In [76]:
x = np.arange(0, plays, 1)
y = map(lambda x: rews[1][x], x)
plt.plot(x, y)
Out[76]:
In [77]:
x = np.arange(0, plays, 1)
y = map(lambda x: rews[2][x], x)
plt.plot(x, y)
Out[77]:
In [11]:
class HalmaState:
""" A state of the game of Halma
"""
def __init__(self, players = 2, rewards = 0):
self.nplayers = 2
self.rewards = 0
self.board = Board(players, rewards)
self.playerJustMoved = self.board.cur_turn
## I changed this -> At the root pretend the player just moved is p2 - p1 has the first move
self.board.reset()
self.size = len(self.board.grid)
def Clone(self):
""" Create a deep clone of this game state.
"""
st = HalmaState()
st.playerJustMoved = self.playerJustMoved
st.board.grid = [self.board.grid[i][:] for i in range(len(self.board.grid))]
return st
def DoMove(self, move):
""" Update a state by carrying out the given move.
Must update playerToMove.
"""
# print move
i, j, k, l = move
self.board.move(self.board.cur_turn, i, j, k, l)
self.playerJustMoved = self.board.cur_turn
def GetMoves(self):
""" Get all possible moves from this state.
"""
moves = {"moves": [], "jumps": []}
for i in range(len(self.board.grid)):
for j in range(len(self.board.grid)):
if self.board.grid[i][j] == self.playerJustMoved:
legals = self.board.getLegalComplete(i, j)
# print legals, self.playerJustMoved, self.board.cur_turn
# remove places we've already traveled this turn if necessary
if legals["moves"]:
moves["moves"] += ([[i, j, k, l] for k, l, dist in legals["moves"] if [k, l] not in self.board.this_turn_visited])
if legals["jumps"]:
moves["jumps"] += ([[i, j, k, l] for k, l, dist in legals["jumps"] if [k, l] not in self.board.this_turn_visited])
# Override
if not moves["moves"] and not moves["jumps"]:
# Find the pieces that are not in the right positions
s = self.board.starting_positions[3 - self.playerJustMoved]
# Find the first missing position
missedPos = [[x,y] for x, y in s if self.board.grid[x][y] == 0]
if missedPos:
target = missedPos[0]
else:
return moves
for i in range(len(self.board.grid)):
for j in range(len(self.board.grid)):
if self.board.grid[i][j] == self.playerJustMoved:
legals = self.board.getLegalComplete(i, j, positive = target)
# print legals, self.playerJustMoved, self.board.cur_turn
# remove places we've already traveled this turn if necessary
if legals["moves"]:
moves["moves"] += ([[i, j, k, l] for k, l, dist in legals["moves"] if [k, l] not in self.board.this_turn_visited])
if legals["jumps"]:
moves["jumps"] += ([[i, j, k, l] for k, l, dist in legals["jumps"] if [k, l] not in self.board.this_turn_visited])
if not moves["moves"] and not moves["jumps"]:
print "something went wrong"
return moves
def GetResult(self, player):
""" Get the game result from the viewpoint of playerjm.
"""
return self.board.checkWin(player)
def __repr__(self):
s= ""
for x in range(len(self.board.grid)):
for y in range(len(self.board.grid[x])):
s += ["[_]","[X]","[O]"][self.board.grid[x][y]]
s += "\n"
return s
In [8]:
class Node:
""" A node in the game tree. Note wins is always from the viewpoint of playerJustMoved.
Crashes if state not specified.
"""
def __init__(self, move = None, moveType = None, parent = None, state = None):
self.move = move # the move that got us to this node - "None" for the root node
self.moveType = moveType
self.parentNode = parent # "None" for the root node
self.childNodes = []
self.wins = 0
self.visits = 0
self.untriedMoves = state.GetMoves() # future child nodes
if not self.untriedMoves:
print "WATTT"
self.playerJustMoved = state.playerJustMoved # the only part of the state that the Node needs later
def UCTSelectChild(self):
""" Use the UCB1 formula to select a child node. Often a constant UCTK is applied so we have
lambda c: c.wins/c.visits + UCTK * sqrt(2*log(self.visits)/c.visits to vary the amount of
exploration versus exploitation.
"""
s = sorted(self.childNodes, key = lambda c: c.wins/c.visits + sqrt(2*log(self.visits)/c.visits))[-1]
return s
def AddChild(self, m, s, moveType = "moves"):
""" Remove m from untriedMoves and add a new child node for this move.
Return the added child node
"""
n = Node(move = m, moveType = moveType, parent = self, state = s)
self.untriedMoves[moveType].remove(m)
self.childNodes.append(n)
return n
def Update(self, result):
""" Update this node - one additional visit and result additional wins. result must be from the viewpoint of playerJustmoved.
"""
self.visits += 1
self.wins += result
def __repr__(self):
return "[M:" + str(self.move) + " MT:" + str(self.moveType) + " W/V:" + str(self.wins) + "/" + str(self.visits) + " U:" + str(self.untriedMoves) + "]"
def TreeToString(self, indent):
s = self.IndentString(indent) + str(self)
for c in self.childNodes:
s += c.TreeToString(indent+1)
return s
def IndentString(self,indent):
s = "\n"
for i in range (1,indent+1):
s += "| "
return s
def ChildrenToString(self):
s = ""
for c in self.childNodes:
s += str(c) + "\n"
return s
In [9]:
def UCT(rootstate, itermax, verbose = False):
""" Conduct a UCT search for itermax iterations starting from rootstate.
Return the best move from the rootstate.
Assumes 2 alternating players (player 1 starts), with game results in the range [0.0, 1.0]."""
rootnode = Node(state = rootstate)
for i in range(itermax):
node = rootnode
state = rootstate.Clone()
# Select
while not node.untriedMoves["moves"] and not node.untriedMoves["jumps"] and node.childNodes != []: # node is fully expanded and non-terminal
node = node.UCTSelectChild()
# print str(state)
state.DoMove(node.move)
# Expand
if node.untriedMoves["moves"] or node.untriedMoves["jumps"]: # if we can expand (i.e. state/node is non-terminal)
m = choice(node.untriedMoves["moves"] + node.untriedMoves["jumps"])
# if m in node.untriedMoves["moves"]:
# node.untriedMoves["moves"].remove(m)
# elif m in node.untriedMoves["jumps"]:
# node.untriedMoves["jumps"].remove(m)
state.DoMove(m)
mt = "moves"
if m in node.untriedMoves["jumps"]:
mt = "jumps"
node = node.AddChild(m, state, mt) # add child and descend tree
mvs = state.GetMoves()
if not mvs:
return None
asdf = 0
# Rollout - this can often be made orders of magnitude quicker using a state.GetRandomMove() function
while mvs["moves"] or mvs["jumps"]: # while state is non-terminal
# print mvs
mv = choice(mvs["moves"] + mvs["jumps"])
if mv in mvs["moves"]:
mvs["moves"].remove(mv)
elif mv in mvs["jumps"]:
mvs["jumps"].remove(mv)
state.DoMove(mv)
# if asdf > 20:
# return
# asdf+=1
# Backpropagate
while node != None: # backpropagate from the expanded node and work back to the root node
node.Update(state.GetResult(node.playerJustMoved)) # state is terminal. Update node with result from POV of node.playerJustMoved
node = node.parentNode
# if i > 2:
# return
# Output some information about the tree - can be omitted
#if (verbose): print(rootnode.TreeToString(0))
#else: print(rootnode.ChildrenToString())
if not rootnode.childNodes:
return rootnode.move
return sorted(rootnode.childNodes, key = lambda c: c.visits)[-1].move # return the move that was most visited
moveRew = -1
winRew = 100
def UCTPlayGame():
""" Play a sample game between two UCT players where each player gets a different number
of UCT iterations (= simulations = tree nodes).
"""
rewards = {1: [], 2: []}
state = HalmaState()
while (state.GetMoves()):
# print(str(state))
if state.playerJustMoved == 1:
m = UCT(rootstate = state, itermax = 10, verbose = False) # play with values for itermax and verbose = True
else:
m = UCT(rootstate = state, itermax = 10, verbose = False)
# print("Best Move: " + str(m) + "\n")
if m:
state.DoMove(m)
rewards[state.playerJustMoved].append(moveRew)
else:
break
if state.GetResult(state.playerJustMoved):
print("Player " + str(state.playerJustMoved) + " wins!")
rewards[state.playerJustMoved].append(winRew)
return state.playerJustMoved, rewards
else:
print("Player " + str(3 - state.playerJustMoved) + " wins!")
rewards[3-state.playerJustMoved].append(winRew)
return 3-state.playerJustMoved, rewards
In [10]:
lol = UCTPlayGame()
In [147]:
print lol
In [148]:
plays= 100
In [150]:
UCTwins = {1: 0, 2: 0}
UCTrews = {1: [], 2: []}
for i in range(plays):
print i
p, r = UCTPlayGame()
UCTwins[p] += 1
UCTrews[1].append(np.sum(r[1]))
UCTrews[2].append(np.sum(r[2]))
UCTcumrews = {1: np.cumsum(UCTrews[1]), 2: np.cumsum(UCTrews[2])}
In [152]:
x = np.arange(0, plays, 1)
y = map(lambda x: UCTrews[1][x], x)
plt.plot(x, y)
Out[152]:
In [153]:
x = np.arange(0, plays, 1)
y = map(lambda x: UCTrews[2][x], x)
plt.plot(x, y)
Out[153]:
In [ ]: