def __init__(self,
num_agents,
num_fire_clusters,
num_fires_per_cluster,
gamma,
fire_locations=None,
start_positions=None,
DT=-1):
EzPickle.__init__(self, num_agents, num_fire_clusters,
num_fires_per_cluster, gamma, fire_locations,
start_positions, DT)
self.discount = gamma
self.DT = DT
self.n_agents = num_agents
self.n_fires = num_fire_clusters * num_fires_per_cluster
self.num_fire_clusters = num_fire_clusters
self.fire_locations = fire_locations
self.start_positions = start_positions
# Assigned on reset()
self.env_agents = [None for _ in range(self.n_agents)] # NEEDED
self.fires = [None for _ in range(self.n_fires)]
self.simpy_env = None
self.uav_events = [] # checks if a UAV needs to act
self.fire_events = [] # checks if a fire was extinguished
self.done = False
self.seed()
def __init__(self, num_agents, num_fires, num_fires_of_each_size, gamma, fire_locations = None, start_positions = None): EzPickle.__init__(self, num_agents, num_fires, num_fires_of_each_size, gamma, fire_locations, start_positions) self.discount = gamma self.n_agents = num_agents self.n_fires = num_fires self.num_fires_of_each_size = num_fires_of_each_size self.fire_locations = fire_locations self.start_positions = start_positions # Assigned on reset() self.env_agents = [None for _ in range(self.n_agents)] # NEEDED self.fires = [None for _ in range(self.n_fires)] self.simpy_env = None self.uav_events = [] # checks if a UAV needs to act self.fire_events = [] # checks if a fire was extinguished self.simtime = 0. self.seed() self.reset()
def __init__(self,
env,
scale_reward=1.,
enable_obsnorm=False,
enable_rewnorm=False,
obs_alpha=0.001,
rew_alpha=0.001,
eps=1e-8):
EzPickle.__init__(self, env, scale_reward, enable_obsnorm,
enable_rewnorm, obs_alpha, rew_alpha, eps)
self._unwrapped = env
self._scale_reward = scale_reward
self._enable_obsnorm = enable_obsnorm
self._enable_rewnorm = enable_rewnorm
self._obs_alpha = obs_alpha
self._rew_alpha = rew_alpha
self._eps = eps
self._flatobs_shape = [None for _ in env.agents]
self._obs_mean = [None for _ in env.agents]
self._obs_var = [None for _ in env.agents]
self._rew_mean = [None for _ in env.agents]
self._rew_var = [None for _ in env.agents]
for agid, agent in enumerate(env.agents):
if isinstance(agent.observation_space, spaces.Box):
self._flatobs_shape[agid] = np.prod(
agent.observation_space.shape)
elif isinstance(env.observation_space, spaces.Discrete):
self._flatobs_shape[agid] = agent.observation_space.n
self._obs_mean[agid] = np.zeros(self._flatobs_shape[agid])
self._obs_var[agid] = np.ones(self._flatobs_shape[agid])
self._rew_mean[agid] = 0.
self._rew_var[agid] = 1.
def __init__(self):
self.discount = GAMMA
self.n_agents = NUM_AGENTS
self.n_fires = NUM_FIRES
# Assigned on reset()
self.env_agents = [None for _ in range(self.n_agents)] # NEEDED
self.fires = [None for _ in range(self.n_fires)]
self.simpy_env = None
self.uav_events = [] # checks if a UAV needs to act
self.fire_events = [] # checks if a fire was extinguished
EzPickle.__init__(self)
self.seed()
self.reset()
def __init__(self): self.fire_extinguish = fire_extinguish() num_agents = self.fire_extinguish.n_uav self.env_agents = [UAV() for _ in range(num_agents)] # NEEDED self.current_state = None self.prev_action = None EzPickle.__init__(self) self.seed() self.reset()
def __setstate__(self, d):
EzPickle.__setstate__(self, d)
self._obs_mean = d['_obs_mean']
self._obs_var = d['_obs_var']
def __getstate__(self):
d = EzPickle.__getstate__(self)
d['_obs_mean'] = self._obs_mean
d['_obs_var'] = self._obs_var
return d