def __init__(self, host, port):
self.socket = GameSocket(host, port)
self.state = State()
self.is_moving_right = True # default: go to right side
self.steps = 0
self.pre_action = 0
def __init__(self,
id,
estWood=-1,
pEnergyToStep=-1,
pStepToGold=-1,
strategy=-1):
self.state = State()
self.info = PlayerInfo(id)
if (estWood == -1): #random strenght
estWood = (5 + randrange(16))
pEnergyToStep = (2 + randrange(9)) * 5
pStepToGold = (1 + randrange(6)) * 50
self.estWood = estWood
self.pEnergyToStep = pEnergyToStep
self.pStepToGold = pStepToGold
#print ("AddG_BOT",estWood,pEnergyToStep,pStepToGold)
self.tx = -1
self.ty = -1
if (strategy == -1):
strategy = np.random.choice(range(6)) - 1
self.selectTargetOption = strategy
def __init__(self, host, port):
self.socket = GameSocket(host, port)
self.state = State()
self.score_pre = (
self.state.score
) # Storing the last score for designing the reward function
def __init__(self, id):
self.state = State()
self.info = PlayerInfo(id)
self.isMovingInc = False
self.isHorizontalMoving = False
def __init__(self, host, port):
self.socket = GameSocket(host, port)
self.state = State()
self.pre_x = 0
self.pre_y = 0
self.pre_energy = 0
#self.pre_action = ''
self.score_pre = self.state.score#Storing the last score for designing the reward function
def __init__(self, host, port):
self.socket = GameSocket(host, port)
self.state = State()
self.score_pre = self.state.score # Storing the last score for designing the reward function
self.decay = 27
self.area_affect = 3
self.affect_eff = 0.92
self.view = None
self.energy_view = None
self.current_action = None
def __init__(self, id, estWood=-1, pEnergyToStep=-1, pStepToGold=-1):
self.state = State()
self.info = PlayerInfo(id)
if (estWood == -1): #random strenght
estWood = (5 + randrange(16))
pEnergyToStep = (2 + randrange(9)) * 5
pStepToGold = (1 + randrange(6)) * 50
self.estWood = estWood
self.pEnergyToStep = pEnergyToStep
self.pStepToGold = pStepToGold
def __init__(self, host, port):
self.socket = GameSocket(host, port)
self.state = State()
self.is_moving_right = True # default: go to right side
self.steps = 0
self.pre_action = 0
self.pre_x = -1
self.pre_y = -1
self.search_left_right = True
self.largest_gold_x = -1
self.largest_gold_y = -1
self.left_or_right = 2
def __init__(self, host, port):
self.socket = GameSocket(host, port)
self.state = State()
# define action space
self.INPUTNUM = 198 # The number of input values for the DQN model
self.ACTIONNUM = 6 # The number of actions output from the DQN model
# define state space
self.gameState = None
self.reward = 0
self.terminate = False
self.score_pre = self.state.score # Storing the last score for designing the reward function
self.energy_pre = self.state.energy # Storing the last energy for designing the reward function
self.viewer = None
self.steps_beyond_done = None
def __init__(self, id):
self.state = State()
self.info = PlayerInfo(id)
self.limit = 2
state_dim = (2 * self.limit + 1)**2 + 3 + 3
action_dim = 6
max_action = 1.0
# load model
kwargs = {
"state_dim": state_dim,
"action_dim": action_dim,
"max_action": max_action,
}
policy_file = "newTD3_Miner_0_2_get_state3"
self.TreeID = 1
self.TrapID = 2
self.SwampID = 3
self.policy = newTD3_bot.TD3(**kwargs)
self.policy.load(f"./models_newTD3_2/{policy_file}")
def __init__(self, id):
self.state = State()
self.info = PlayerInfo(id)
self.limit = 2
state_dim = (2*self.limit+1)**2 + 3
action_dim = 6
max_action = 1.0
# load model
kwargs = {
"state_dim": state_dim,
"action_dim": action_dim,
"max_action": max_action,
}
policy_file = "DDPG_Miner_0_2"
self.TreeID = 1
self.TrapID = 2
self.SwampID = 3
self.policy = DDPG.DDPG(**kwargs)
self.policy.load(f"./models_DDPG/{policy_file}")
def __init__(self, id):
self.state = State()
self.info = PlayerInfo(id)
def __init__(self, id):
self.state = State()
self.info = PlayerInfo(id)
self.path = None
self.grid = next_move([[0 for i in range(9)] for j in range(21)])
self.idx = 0
def __init__(self, id):
self.state = State()
self.info = PlayerInfo(id)
self.isMovingInc = False
self.initial_flag = True