def reset_world(self, world):
# random properties for agents
# add agents
world.agents = [MortalAgent() for i in range(self.num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
agent.silent = True
agent.terminated = False
agent.size = _AGENT_SIZE
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
agent.color = np.array([0.35, 0.35, 0.85])
agent.previous_observation = None
# shuffle landmarks to make sure hazard is not in same index
shuffle(world.landmarks)
for landmark in world.landmarks:
landmark.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
landmark.state.p_vel = np.zeros(world.dim_p)
# properties for landmarks
if isinstance(landmark, RiskRewardLandmark) and landmark.is_hazard:
#TODO: make colors heatmap of risk probability over all bounds
landmark.color = np.array([
landmark.risk_fn.get_failure_probability(0, 0) + .1, 0, 0
])
landmark.hazard_tag = 1.0
else:
landmark.color = np.array([0.25, 0.25, 0.25])
landmark.hazard_tag = 0.0
def reset_world(self, world):
# add agents with random properties
world.agents = [MortalAgent() for i in range(self.num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.terminated = False
agent.collide = True
agent.silent = True
agent.size = DP.agent_size
agent.color = np.array([0.35, 0.35, 0.85])
# random properties for landmarks
for i, landmark in enumerate(world.landmarks):
landmark.color = np.array([0.25, 0.25, 0.25])
goal = np.random.choice(world.landmarks)
goal.color = np.array([0.15, 0.65, 0.15])
for i, obstacle in enumerate(world.obstacles):
obstacle.color = np.array([0.90, 0.40, 0.40])
# set random initial states
for agent in world.agents:
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
for landmark in world.landmarks:
landmark.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
landmark.state.p_vel = np.zeros(world.dim_p)
for obstacle in world.obstacles:
obstacle.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
obstacle.state.p_vel = np.zeros(world.dim_p)
def reset_world(self, world):
# find agent size as function of number of agents baselined off simple_spread 3-agent case
agent_size = 0.15 * np.sqrt(3.0 / float(self.num_agents))
# random properties for agents
# add agents
world.agents = [MortalAgent() for i in range(self.num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent_%d' % i
agent.collide = True
agent.silent = True
agent.terminated = False
agent.size = agent_size
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
agent.color = np.array([0.35, 0.35, 0.85])
agent.previous_observation = None
# shuffle landmarks to make sure hazard is not in same index
shuffle(world.landmarks)
for landmark in world.landmarks:
# rename landmarks to preserve label ordering in joint state (see mager/environment.py:get_joint_state)
landmark.name = 'landmark_%d' % i
landmark.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
landmark.state.p_vel = np.zeros(world.dim_p)
landmark.hazard_tag = 0.0
landmark.color = np.array([0.25, 0.25, 0.25])
def reset_world(self, world):
# random properties for agents
# add agents
world.agents = [MortalAgent() for i in range(self.num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.terminated = False
agent.size = _AGENT_SIZE
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
agent.color = np.array([0.35, 0.35, 0.85])
def reset_world(self, world):
# random properties for agents
# add agents
world.agents = [MortalAgent() for i in range(self.num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.terminated = False
agent.size = _AGENT_SIZE
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
agent.color = np.array([0.35, 0.35, 0.85])
agent.previous_observation = None
# shuffle landmarks to make sure hazard is not in same index
for landmark in world.landmarks:
landmark.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
landmark.state.p_vel = np.zeros(world.dim_p)
def reset_world(self, world):
# random properties for agents
# add agents
world.agents = [MortalAgent() for i in range(self.num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.terminated = False
agent.size = _AGENT_SIZE
agent.max_observation_distance = _MAX_OBSERVATION_DISTANCE
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
agent.color = np.array([0.35, 0.35, 0.85])
for landmark in world.landmarks:
landmark.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
landmark.state.p_vel = np.zeros(world.dim_p)
# randomize terminal locations, but regularize to ensure conistent distances
origin_state, destination_state = self.spawn_terminals(world)
world.origin_terminal_landmark.state.p_pos = origin_state
world.destination_terminal_landmark.state.p_pos = destination_state