def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.state = 0 #State0 try to find exit, State1 bomb is planted run away
self.bombTimer = 0
self.bombX = 0
self.bombY = 0
self.bombActive = 0
def restart(self, wrld):
CharacterEntity.__init__(self, self.name, self.avatar, self.startX,
self.startY)
self.agentX, self.angetY = self.startX, self.startY
self.agentLX, self.agentLY = self.startX, self.startY
self.bombTimer = 11
self.bombX, self.bombY = -1, -1
def __init__(self, n, d, x, y, wrld):
CharacterEntity.__init__(self, n, d, x, y)
#self.pathMaker = Astar(wrld)
#self.path = self.pathMaker.findpathtoend(self.x, self.y)
#print('path length: ', len(self.path))
self.path = self.makepath(wrld)
self.i = 0
def __init__(
self,
name,
avatar,
x,
y,
):
CharacterEntity.__init__(self, name, avatar, x, y)
self.exit = None
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.state = "go"
self.hasMoved = False
self.dxdy = (-1, -1)
self.bomb_locations = [(7, 2, True), (7, 6, True), (7, 10, True),
(7, 12, True), (7, 18, False)]
self.location_index = 0
def __init__(self, name, player, x, y, weights):
CharacterEntity.__init__(self, name, player, x, y)
self.learning_rate = 0.2
self.discount_factor = 0.9
self.epsilon = 0.2
self.last_q = 0
self.current_action = (0, 0)
self.weights = weights
self.current_pos = (0, 0)
self.last_pos = (0, 0)
def __init__(
self,
name,
avatar,
x,
y,
):
CharacterEntity.__init__(self, name, avatar, x, y)
self.bomb_timer = 0
self.loc = []
def __init__(self, name, avatar, x, y, varient=1):
CharacterEntity.__init__(self, name, avatar, x, y)
self.varient = varient
self.path = []
# (x,y) tuple for location of the exit
self.goal = None
self.bombs = []
self.toBomb = (4, 2)
self.newbomb_flag = 0
self.old_state = None
self.timer = -1
self.state = STATE_SNEAK
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.learning_limit = 100
self.learning_step = self.learning_limit
self.is_learning = False
self.discount = 0.9
self.epsilon_start = 0.95
self.epsilon = self.epsilon_start
self.epsilon_rate = 0.3 # How fast should epsilon decrease
self.path = []
self.path_search = 0
self.danger_radius = 5
seed(10)
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.name = name
self.avatar = avatar
self.startX, self.startY = x, y
self.wrld = None
self.bombPlaced = False
self.bombTimer = 11
self.agentX, self.agentY = self.startX, self.startY
self.agentLX, self.agentLY = self.startX, self.startY
self.exitX, self.exitY = -1, -1
self.bombX, self.bombY = -1, -1
self.locations = set('0,0')
def __init__(self, name, avatar, x, y, inter):
CharacterEntity.__init__(self, name, avatar, x, y)
self.name = name
self.avatar = avatar
self.startX, self.startY = x, y
self.wrld = None
self.bombPlaced = False
self.bombTimer = 11
self.agentX, self.agentY = self.startX, self.startY
self.agentLX, self.agentLY = self.startX, self.startY
self.exitX, self.exitY = -1, -1
self.bombX, self.bombY = -1, -1
self.inter = inter
self.lastState = ''
self.QTable = ""
self.readQTable()
self.nextAction = 0
def __init__(self,name,avatar,x,y, qFile, learn):
CharacterEntity.__init__(self,name,avatar,x,y)
self.name = name
self.avatar = avatar
self.startX, self.startY = x,y
self.wrld = None
self.bombPlaced = False
self.bombTimer = 10
self.agentX, self.agentY = self.startX,self.startY
self.agentLX,self.agentLY = self.startX,self.startY
self.exitX, self.exitY = -1,-1
self.bombX, self.bombY = -1, -1
self.lastState = ''
self.lastAction = ''
self.q_file = qFile
self.q_table =self.init_q(qFile)
self.learn = learn
def __init__(self, name, avatar, x, y, q_learner, train, iteration): CharacterEntity.__init__(self, name, avatar, x, y) self.q_learner = q_learner self.train = train self.iteration = iteration self.epsilon = 1 / (self.iteration + 1) ** 0.5 self.prev_wrld = None self.best_wrld = None self.iterations = 0 self.qLearning = False self.bomb = False self.state = "go" self.dxdy = (-1, -1) self.bomb_locations = [(0, 2, True), (0, 3, True),(1, 3, True), (2, 3,True), (3, 3, True),(4, 3, True),(5, 3, True), (7, 3, True), (7, 10, True), (4, 9, False), (7, 12, True), (7, 18, False)] self.location_index = 0
def __init__(self, name, avatar, x, y, active_features, decay, lr):
CharacterEntity.__init__(self, name, avatar, x, y)
# Weights turned on (if 0 in 6th spot 6th feature turned off)
self.on = [0.0] * self.NUM_FEATURES
for feat_num, weight in active_features:
self.on[feat_num] = weight
self.weightArray = self.on # Array of weights
self.featureArray = [0.0] * self.NUM_FEATURES # Array of features
self.gamma = 0.9 # Reward Decay
self.lr = lr # Learning Rate
self.decay = decay # Decay
self.wins = 0 # Number of wins so far
self.losses = 0 # Number of losses so far
self.debug = False # Turn off to reduce prints
self.oldState1 = self.on # Used to save a state to revert back to later
self.oldState2 = [
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -5.0, 0.0, 0.0, 0.0, 0.0, 0.0
] # Used to save rush state
self.state = 1 # State the bot is currently in
self.monster_aggro_range = 2
def __init__(self,
name,
avatar,
x,
y,
q_learner,
train,
iteration,
stateMachine=False):
CharacterEntity.__init__(self, name, avatar, x, y)
self.q_learner = q_learner
self.train = train
self.iteration = iteration
self.epsilon = 1 / (self.iteration + 1)**0.5
self.prev_wrld = None
self.best_wrld = None
self.count = 0
self.iterations = 0
self.pastMoves = []
self.identity = "A-Star"
self.stateMachine = stateMachine
def __init__(self, name, avatar, x, y, sensitivity):
CharacterEntity.__init__(self, name, avatar, x, y)
# sensitivity is a number that weight the distance to monster evaluation
# higher value means stay further away from nearest monster (usually 100~1000)
self.sensitivity = sensitivity
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.ticked = False
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.ticked = False
self.oldwrld = None
self.currwrld = None
def __init__(self, name, avatar, x, y, scenario_num, variant_num): CharacterEntity.__init__(self, name, avatar, x, y) self.scenario_num = scenario_num self.variant_num = variant_num
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.monster_dist = 1
self.best = 10000000
self.worst = -self.best * 1000
self.max_depth = 2
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
def __init__(self, name, avatar, x, y, d):
CharacterEntity.__init__(self, name, avatar, x, y)
self.sensitivity = d # d is distance to monster ,higher means stay further away from a monster near u
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.first = True
self.path = None
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.state = 'm'
self.bomb_at = []
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.reward = 0
self.q_learn = Qlearning(0)
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.state = "aStar"
def __init__(self, name, avatar, x, y):
CharacterEntity.__init__(self, name, avatar, x, y)
self.need_search = True
self.movelist = []