def __init__(self, actions, two_sided=False):
self._actions = actions #[-1, 0, 1]
self._train = True
self._x_bins = utils.X_BINS
self._y_bins = utils.Y_BINS
self._v_x = utils.V_X
self._v_y = utils.V_Y
self._paddle_locations = utils.PADDLE_LOCATIONS
self._num_actions = utils.NUM_ACTIONS
# Create the Q Table to work with
self.Q = utils.create_q_table()
self.two_sided = two_sided
self.prev_action = 0
self.prev_state = [0, 0.5, 0, 0, 0.8]
self.N = utils.create_q_table()
self.pbounce = 0
self.first = True
self.itrs = 0
self.explore = True
self.explore_print = True
self.epsilon = 1
self.decay = 0.999
self.min_epsilon = .001
self.cdecay = .9
self.c_val = 50
self.min_c = 30
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
self.Ne = Ne # used in exploration function
self.C = C
self.gamma = gamma
# Create the Q and N Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
self.Ne = Ne # used in exploration function
self.C = C
self.gamma = gamma
# Create the Q and N Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table(
) #is this a count of how many times that state has been visited?
self.reset()
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
actions.reverse()
self.actions_priority = actions
self.Ne = Ne # used in exploration function
self.C = C
self.gamma = gamma
self.reset()
# Create the Q and N Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
self.Ne = Ne # used in exploration function
self.C = C
self.gamma = gamma
self.s = None
self.a = None
self.points = 0
# Create the Q and N Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
# reset in init maybe
self.reset()
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
self.Ne = Ne # used in exploration function
self.C = C
self.gamma = gamma
self.first = True
self.track_actions = []
self.s = None
self.a = None
# Create the Q and N Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
def __init__(self, actions, two_sided=False):
self.two_sided = False
self._actions = actions
self._train = True
self._x_bins = utils.X_BINS
self._y_bins = utils.Y_BINS
self._v_x = utils.V_X
self._v_y = utils.V_Y
self._paddle_locations = utils.PADDLE_LOCATIONS
self._num_actions = utils.NUM_ACTIONS
# Create the Q Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
self.last_state = None
self.games = 0
self.prev_bounce = 0
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
self.Ne = Ne # used in exploration function
print("Ne", Ne)
print("gamma", gamma)
self.C = C # constant for learning rate
self.gamma = gamma # discount
# Create the Q and N Table to work with
# At the beginning, it should be all zeros for Q-table and N-table
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
self.points = 0
self.s = None
self.a = None #?
def __init__(self, actions, Ne, C, gamma):
self.actions = actions
self.Ne = Ne # used in exploration function
self.C = C
self.gamma = gamma
# Create the Q and N Table to work with
self.Q = utils.create_q_table()
self.N = utils.create_q_table()
#last state
self.s = None
#last action
self.a = None
#points
self.points = 0
#begin
self.begin = False
def __init__(self, actions, two_sided=False):
self.two_sided = two_sided
self._actions = actions
self._train = True
self._x_bins = utils.X_BINS
self._y_bins = utils.Y_BINS
self._v_x = utils.V_X
self._v_y = utils.V_Y
self._paddle_locations = utils.PADDLE_LOCATIONS
self._num_actions = utils.NUM_ACTIONS
# Create the Q Table to work with
self.Q = utils.create_q_table()
self.SApair = utils.create_q_table()
self.prev_state = [6, 6, 1, 1, 6]
self.prev_action = 0
self.prev_bounces = 0
self.dis_fac = 0.8
self.lrate = 6
self.epsilon = 0.6
def __init__(self, actions, two_sided=False):
self.old_state = [-1, -1, -1, -1, -1]
self.old_action = 1
self.max_bounces = 0
self.learning_rate = LEARNING_CONSTANT / (LEARNING_CONSTANT + 1)
self.discount_rate = DISCOUNT_RATE / (DISCOUNT_RATE + 1)
self.epsilon = EPSILON / (EPSILON + 1)
self.two_sided = two_sided
self.N = utils.create_q_table()
self._actions = actions
self._train = True
self._x_bins = utils.X_BINS
self._y_bins = utils.Y_BINS
self._v_x = utils.V_X
self._v_y = utils.V_Y
self._paddle_locations = utils.PADDLE_LOCATIONS
self._num_actions = utils.NUM_ACTIONS
# Create the Q Table to work with
self.Q = utils.create_q_table()
def __init__(self, actions, two_sided=False):
self._actions = actions
self._train = True
self._x_bins = utils.X_BINS
self._y_bins = utils.Y_BINS
self._v_x = utils.V_X
self._v_y = utils.V_Y
self._paddle_locations = utils.PADDLE_LOCATIONS
self._num_actions = utils.NUM_ACTIONS
# Create the Q Table to work with
self.Q = utils.create_q_table()
self.last_x_dir = self._v_x
self.games_played = 0
self.epsilon = .5
self.alpha = .2
self.gamma = .9
self.prev_state = None
self.prev_action = None
self.prev_reward = None
self.N = self.Q.copy()
import utils
