def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_good_agents = 1
num_adversaries = 2
num_agents = num_adversaries + num_good_agents
num_landmarks = 1
num_borders = 80 # (20 * 4)
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.075 if agent.adversary else 0.05
agent.accel = 3.0 if agent.adversary else 4.0
#agent.accel = 20.0 if agent.adversary else 25.0
agent.max_speed = 1.0 if agent.adversary else 1.3
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
landmark.boundary = False
# add borders
"""
shapes = [[[0.0, 0.0], [1.95, 0.0], [1.95, 0.05], [0.0, 0.05]], \
[[0.0, 0.0], [0.05, 0.0], [0.05, 1.95], [0.0, 1.95]], \
[[0.0, 0.0], [1.95, 0.0], [1.95, 0.05], [0.0, 0.05]], \
[[0.0, 0.0], [0.05, 0.0], [0.05, 1.95], [0.0, 1.95]]]
"""
world.borders = [Border() for i in range(num_borders)]
for i, border in enumerate(world.borders):
border.name = 'border %d' % i
border.collide = True
border.movable = False
border.size = 0.15
border.boundary = False
# border.shape = [[-0.05, -0.05], [0.05, -0.05], [0.05, 0.05], [-0.05, 0.05]]
border.shape = [[-0.1, -0.1], [0.1, -0.1], [0.1, 0.1], [-0.1, 0.1]]
#print(border.pos)
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
# main configurations
num_agents = 2
num_hills = 2
num_switches = 1
self.max_episode_length = 100
# create hills (on edges)
possible_hill_positions = [
np.array([-0.8, 0]),
np.array([0, 0.8]),
np.array([0.8, 0]),
np.array([0, -0.8])
]
hill_positions = random.sample(possible_hill_positions, k=num_hills)
hills = [Hill(hill_positions[i]) for i in range(num_hills)]
# create switches (in corners)
possible_switch_positions = [
np.array([-0.8, -0.8]),
np.array([-0.8, 0.8]),
np.array([0.8, -0.8]),
np.array([0.8, 0.8])
]
switch_positions = random.sample(possible_switch_positions,
k=num_switches)
switches = [Switch(switch_positions[i]) for i in range(num_switches)]
# make world and set basic properties
world = SwitchWorld(hills, switches)
world.dim_c = 2
world.collaborative = True
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.size = 0.1
agent.accel = 5.0
agent.max_speed = 5.0
if i == 0:
agent.color = np.array([0.35, 0.35, 0.85])
else:
agent.color = np.array([0.35, 0.85, 0.85])
# make initial conditions
self.reset_world(world)
return world
def make_world(self, staged=False, set_trap=True, use_dense_rewards=False):
world = World()
world.use_dense_rewards = use_dense_rewards
# set any world properties first
self.staged = staged
self.set_trap = set_trap
num_agents = 2
num_landmarks = 2 * num_agents
self.num_walls = 4 + int(self.staged)
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
landmark.size *= 4
landmark.is_activated = False
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
if i == 0:
agent.role = 'imitator'
agent.clip_positions = np.array(
[[-world.scale, .55 * world.scale],
[world.scale, world.scale]])
agent.landmarks = [world.landmarks[2], world.landmarks[3]]
self.trap_width = agent.size * 4.
elif i == 1:
agent.role = 'demonstrator'
agent.clip_positions = np.array(
[[-world.scale, -world.scale],
[world.scale, .45 * world.scale]])
agent.landmarks = [world.landmarks[0], world.landmarks[1]]
else:
raise ValueError(
'There should only be two agents in this scenario')
# add walls to force the "leader" through a longer path
world.walls = [Wall() for i in range(self.num_walls)]
if self.set_trap:
world.trap = Wall()
world.walls.append(world.trap)
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 4
#world.damping = 1
num_good_agents = 1
num_adversaries = 2
num_agents = num_adversaries + num_good_agents
num_landmarks = 1
num_food = 1
num_forests = 2
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.leader = True if i == 0 else False
agent.silent = True if i > 0 else False
agent.adversary = True if i < num_adversaries else False
agent.size = 0.075 if agent.adversary else 0.045
agent.accel = 3.0 if agent.adversary else 4.0
#agent.accel = 20.0 if agent.adversary else 25.0
agent.max_speed = 1.0 if agent.adversary else 1.3
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
landmark.boundary = False
world.food = [Landmark() for i in range(num_food)]
for i, landmark in enumerate(world.food):
landmark.name = 'food %d' % i
landmark.collide = False
landmark.movable = False
landmark.size = 0.03
landmark.boundary = False
world.forests = [Landmark() for i in range(num_forests)]
for i, landmark in enumerate(world.forests):
landmark.name = 'forest %d' % i
landmark.collide = False
landmark.movable = False
landmark.size = 0.3
landmark.boundary = False
world.landmarks += world.food
world.landmarks += world.forests
#world.landmarks += self.set_boundaries(world) # world boundaries now penalized with negative reward
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
num_humans = 2
num_zombies = 5
num_agents = num_humans + num_zombies
# add agents
agents = []
# add humans' team
for i in range(num_humans):
agent = Agent()
agent.collide = True
agent.team = 0
agent.name = 'human %d' % i
agent.size = 0.05
agent.accel = 4.0
agent.max_speed = 1.3
agent.health_decay = 0.99
agents.append(agent)
# add zombies' team
for i in range(num_zombies):
agent = Agent()
agent.collide = True
agent.team = 1
agent.name = 'zombie %d' % i
agent.size = 0.05
agent.accel = 3.0
agent.max_speed = 1.0
agents.append(agent)
world.agents = agents
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_agents = self.num_agents
num_landmarks = self.num_agents
num_obstacles = 12
# generate one-hot encoding for unique hidden goals
self.one_hot_array = list(itertools.product([0, 1], repeat=num_landmarks))
# generate colours for goal identification
for _ in range(num_landmarks):
self.colours.append(np.random.uniform(-1, +1, 3))
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.size = 0.10
agent.color = self.colours[i]
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
landmark.color = self.colours[i]
landmark.id = self.one_hot_array[2**i]
self.occupied_landmarks.append(0)
# add obstacles
world.obstacles = [Landmark() for i in range(num_obstacles)]
for i, obstacle in enumerate(world.obstacles):
obstacle.name = 'obstacle %d' % i
obstacle.collide = True
obstacle.movable = False
obstacle.size = 0.40
obstacle.boundary = False
obstacle.color = np.array([0.25, 0.25, 0.25])
# self.create_wall(world, obstacle, 10, -0.2, -1, -0.2, -0.2)
# make initial conditions
for i, agent in enumerate(world.agents):
agent.state.p_pos = np.array(self.sample_position())
if i > 0:
self.check_for_spawn_clash(world.agents, agent)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
self.assign_goals(i, agent)
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.cache_dists = True
world.dim_c = 2
num_agents = 8
num_collectors = 6
num_deposits = num_agents - num_collectors
world.treasure_types = list(range(num_deposits))
world.treasure_colors = np.array(
sns.color_palette(n_colors=num_deposits))
num_treasures = num_collectors
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.i = i
agent.name = 'agent %d' % i
agent.collector = True if i < num_collectors else False
if agent.collector:
agent.color = np.array([0.85, 0.85, 0.85])
else:
agent.d_i = i - num_collectors
agent.color = world.treasure_colors[agent.d_i] * 0.35
agent.collide = True
agent.silent = True
agent.ghost = True
agent.holding = None
agent.size = 0.05 if agent.collector else 0.075
agent.accel = 1.5
agent.initial_mass = 1.0 if agent.collector else 2.25
agent.max_speed = 1.0
# add treasures
world.landmarks = [Landmark() for i in range(num_treasures)]
for i, landmark in enumerate(world.landmarks):
landmark.i = i + num_agents
landmark.name = 'treasure %d' % i
landmark.respawn_prob = 1.0
landmark.type = np.random.choice(world.treasure_types)
landmark.color = world.treasure_colors[landmark.type]
landmark.alive = True
landmark.collide = False
landmark.movable = False
landmark.size = 0.025
landmark.boundary = False
world.walls = []
# make initial conditions
self.reset_world(world)
self.reset_cached_rewards()
return world
def make_world(self):
world = World()
# add agents
world.agents = [Agent() for i in range(numAgents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.sight = 0.2
agent.size = 0.05
agent.max_speed = 0.3
# make initial conditions
self.reset_world(world)
return world
def make_world(self, config):
self.shaping = config.shaping
self.predators_comm = config.predators_comm
world = World()
world.randomPreySpeed = True if config.prey_max_speed == 'random' else False
# set any world properties first
world.dim_c = config.predators_comm_size if config.predators_comm else 0
num_prey = config.num_prey
num_predators = config.num_predators
num_agents = num_predators + num_prey
num_landmarks = config.num_landmarks
# add walls
if config.bound_world:
world.walls.append(Wall(orient='H', axis_pos=1.3, endpoints=(-2, 2), width=0.2, hard=True))
world.walls.append(Wall(orient='H', axis_pos=-1.3, endpoints=(-2, 2), width=0.2, hard=True))
world.walls.append(Wall(orient='V', axis_pos=1.3, endpoints=(-2, 2), width=0.2, hard=True))
world.walls.append(Wall(orient='V', axis_pos=-1.3, endpoints=(-2, 2), width=0.2, hard=True))
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.id = i
agent.collide = True
agent.adversary = True if i < num_predators else False
# if config.predators_comm:
# agent.silent = False if agent.adversary else True # Oren
# else:
# agent.silent = True
agent.silent = True
agent.size = 0.075 if agent.adversary else 0.05
# agent.accel = 3.0 if agent.adversary else 2.0
# agent.max_speed = 1.0 if agent.adversary else 0.5
agent.accel = config.pred_acc if agent.adversary else config.prey_acc
agent.max_speed = config.pred_max_speed if agent.adversary else config.prey_max_speed
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
landmark.boundary = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_agents = FLAGS.num_uav
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
agent.silent = True
agent.max_speed = FLAGS.max_speed / FLAGS.map_scale_rate / 0.1
agent.size = FLAGS.radius / FLAGS.map_scale_rate
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
# self.num_groups = cfg.gs.num_groups
# self.num_landmarks = cfg.gs.num_landmarks
# self.has_collision = cfg.gs.has_collision # individual can/cannot overlap
# self.has_comm = cfg.gs.has_comm # individual can/cannot communicate
# self.different_landmarks = cfg.gs.different_landmarks # targets of different groups are/aren't different.
# # world.collaborative = True
# self.group_colours = cfg.gs.group_colours
self.num_groups = 2
self.num_landmarks = 3
self.has_collision = False # individual can/cannot overlap
self.has_comm = False # individual can/cannot communicate
self.different_landmarks = True # targets of different groups are/aren't different.
# world.collaborative = True
self.group_colours = [[0.35, 0.35, 0.85], [0.35, 0.85, 0.35]]
assert (len(self.group_colours) == self.num_groups)
# add agents
num_agents = self.num_groups * self.num_landmarks
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d group %d' % (i, i // self.num_landmarks)
agent.collide = self.has_collision
agent.silent = not self.has_comm
agent.size = 0.15
# add landmarks
total_landmarks = \
num_agents if self.different_landmarks else \
self.num_landmarks
world.landmarks = [Landmark() for i in range(total_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = ('landmark %d' % i) \
+ (' group %d' % (i // self.num_landmarks) \
if self.different_landmarks else '')
landmark.collide = False
landmark.movable = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# add agents
world.agents = [Agent() for i in range(1)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
agent.silent = True
# add landmarks
world.landmarks = [Landmark() for i in range(1)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self, team_size=1):
world = World()
world.use_walls = True
world.goal_width = 0.20
# set any world properties first
world.dim_c = 2
num_good_agents = team_size
num_adversaries = team_size
num_agents = num_adversaries + num_good_agents
num_landmarks = 1
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.06
agent.accel = 2.0
agent.kicking = True
angle = np.linspace(0, 2 * np.pi, 16,
endpoint=False)[np.newaxis, :]
agent.kicks = np.concatenate([np.cos(angle),
np.sin(angle)]).T * 2.35
agent.discrete_action_space = False
agent.max_speed = 0.75
agent.is_ball = False
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
landmark = world.landmarks[0]
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = True
landmark.size = 0.06
landmark.is_ball = True
landmark.adversary = -1
# make initial conditions
def done(agent, world):
return self.is_goal(world)
world.is_scenareo_over = done
self.reset_world(world)
return world
def make_world(self, graph_obs=False):
world = World()
world.graph_obs = graph_obs
# set any world properties first
world.dim_c = 2
num_good_agents = 4
num_adversaries = 4
num_agents = num_adversaries + num_good_agents
num_landmarks = 2
num_walls = 0
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.075 if agent.adversary else 0.05
agent.accel = 3.0 if agent.adversary else 4.0
#agent.accel = 20.0 if agent.adversary else 25.0
agent.max_speed = 1.0 if agent.adversary else 1.3
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
landmark.boundary = False
world.walls = [Wall() for i in range(num_walls)]
for i, wall in enumerate(world.walls):
wall.name = 'wall %d' % i
wall.collide = True
wall.movable = False
wall.size = 0.0
wall.boundary = False
if num_walls != 0:
world.walls[0].state.p_pos = np.asarray([1, 0])
world.walls[1].state.p_pos = np.asarray([0, 1])
world.walls[2].state.p_pos = np.asarray([-1, 0])
world.walls[3].state.p_pos = np.asarray([0, -1])
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
num_good_agents = 2
num_adversaries = 2
num_balloons = 5
num_landmarks = 3
vocabulary_size = 2
world.dim_c = vocabulary_size
num_agents = num_adversaries + num_good_agents
# add agents
world.agents = [Agent() for _ in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.index = i
agent.collide = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.1 if agent.adversary else 0.1
agent.accel = 3.0 if agent.adversary else 4.0
agent.max_speed = 1.0 if agent.adversary else 1.3
# Added attributes for balloons and observation range
agent.num_balloons = num_balloons
agent.init_num_balloons = num_balloons
agent.obs_range = 3.0 if agent.adversary else 3.0
agent.atk_range = 0.5 if agent.adversary else 0.5
agent.team = 0 if agent.adversary else 1
agent.state.c = np.zeros((num_agents, world.dim_c), dtype=int)
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.1
landmark.boundary = False
# make initial conditions
self.obs = {}
self.reset_world(world)
return world
def make_world(self):
print("**********liyuan scenario*************")
world = World()
# set any world properties first
world.dim_c = 2
num_good_agents = 3
num_adversaries = 3
num_agents = num_adversaries + num_good_agents
num_landmarks = 0
self.num_green = copy.deepcopy(num_good_agents)
self.num_red = copy.deepcopy(num_adversaries)
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.04 if agent.adversary else 0.04
# agent.accel = 3.0 if agent.adversary else 2.0
agent.accel = 2.0 if agent.adversary else 2.0
# agent.accel = 20.0 if agent.adversary else 25.0
# agent.max_speed = 1.5 if agent.adversary else 1.2
# agent.max_speed = 1.0 if agent.adversary else 1.0
agent.max_speed = 1.0 if agent.adversary else 0.5 ###changed by liyuan
agent.death = False
agent.chi = np.array([0.1, 0])
if agent.adversary:
agent.lock_num = [0 for j in range(num_good_agents)]
else:
agent.lock_num = [0 for j in range(num_adversaries)]
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
landmark.boundary = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self, args):
if 'shared_obs' in args.keys():
self.shared_obs = args['shared_obs']
else:
self.shared_obs = True
if ('boundary' in args.keys()) and (args['boundary'] is not None):
world = World(boundary=args['boundary'])
else:
world = World()
# set any world properties first
world.dim_c = 2
if ('num_agents' in args.keys()) and (args['num_agents'] is not None):
num_agents = args['num_agents']
else:
num_agents = 3
self.num_agents = num_agents
if ('num_landmarks' in args.keys()) and (args['num_landmarks']
is not None):
num_landmarks = args['num_landmarks']
else:
num_landmarks = 3
self.num_landmarks = num_landmarks
world.collaborative = True
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = False
agent.size = 0.15
agent.id = i
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
# make initial conditions
self.reset_world(world)
self.self_obs_indices = np.arange(2 * world.dim_p +
num_landmarks * world.dim_p)
return world
def make_world(self, n_agents, config, prob_random):
"""
n_agents - number of agents (also equal to number of target landmarks)
config - dictionary
prob_random - probability of random agent and landmark initial locations
"""
world = World()
# set any world properties first
world.dim_c = 0
self.n_agents = n_agents
self.agents_x = config['agents_x']
self.agents_y = config['agents_y']
self.landmarks_x = config['landmarks_x']
self.landmarks_y = config['landmarks_y']
# standard deviation of Gaussian noise on initial agent location
self.initial_std = config['initial_std']
self.prob_random = prob_random
num_agents = n_agents
num_landmarks = n_agents
# deliberate False, to prevent environment.py from sharing reward
world.collaborative = False
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.idx = i
agent.collide = True
agent.silent = True
agent.size = 0.15
# agent.size = 0.1
agent.reached = False
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.idx = i
landmark.collide = False
landmark.movable = False
# landmark.size = 0.05
# read colors
# self.colors = np.loadtxt('colors.csv', delimiter=',')
self.colors = colors
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_agents = 3
num_landmarks = 8
world.collaborative = True
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
if i == 0:
agent.name = 'poacher'
agent.size = 0.075
agent.id = 1
agent.accel = 2
agent.max_speed = 1
agent.sight = 0.3
agent.color = np.array([0.85, 0.35, 0.35])
if i == 1:
agent.name = 'ranger'
agent.size = 0.075
agent.id = 2
agent.accel = 2.15
agent.max_speed = 1
agent.sight = 0.3
agent.color = np.array([0.35, 0.35, 0.85])
if i == 2:
agent.name = 'uav'
agent.size = 0.05
agent.id = 3
agent.accel = 3
agent.max_speed = 1.3
agent.sight = 0.5
agent.color = np.array([0.35, 0.85, 0.35])
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'animal %d' % i
landmark.collide = False
landmark.movable = False
landmark.collisionTimes = 0
landmark.captured = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self, mode):
world = World()
self.mode = mode
# add agents
world.agents = [Agent() for i in range(2)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.size = 0.1
# add boxes
n_box = 1 # One box and pushing to left
self.boxes = [Landmark() for _ in range(n_box)]
for i, box in enumerate(self.boxes):
box.name = 'box %d' % i
box.collide = True
box.movable = True
box.size = 0.25
box.initial_mass = 7.
box.index = i
world.landmarks.append(box)
# add targets
self.targets = [Landmark() for _ in range(2)]
for i, target in enumerate(self.targets):
target.name = 'target %d' % i
target.collide = False
target.movable = False
target.size = 0.05
target.index = i
world.landmarks.append(target)
# add goals (used only for vis)
world.goals = [Goal() for i in range(len(world.agents))]
for i, goal in enumerate(world.goals):
goal.name = 'goal %d' % i
goal.collide = False
goal.movable = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_agents = 2
num_landmarks = num_agents + 1
num_goals = num_agents
world.collaborative = True
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
agent.silent = True
agent.size = 0.15
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
# Add landmarks
if i == 0 or i == 1:
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
landmark.size = 0.10
elif i == 2:
# Add oracle
landmark.name = "oracle"
landmark.collide = False
landmark.movable = False
landmark.oracle_on = False
landmark.size = 0.10
else:
raise ValueError()
# add goals (used only for vis)
world.goals = [Goal() for i in range(num_goals)]
for i, goal in enumerate(world.goals):
goal.name = 'goal %d' % i
goal.collide = False
goal.movable = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
world.es = Geo_env(coord_len=12,red_line_total=red_line_total)
world.red = world.es.red_line
world.red_init = world.red
world.norm = [(world.es.red_line_maxx-world.es.red_line_minx),(world.es.red_line_maxy-world.es.red_line_miny)]
# add agents
world.agents = [Agent() for i in range(world.es.coord_len)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.index = i
agent.collide = False
agent.silent = True
agent.adversary = False
agent.color = np.array([0.25,0.25,0.25])
self.reset_world(world)
return world
def make_world(self):
# world object keeps list of agents and entities (can change at execution-time!)
world = World()
# add agents
world.agents = [Agent() for i in range(1)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
agent.silent = True
# add landmarks
world.landmarks = [Landmark() for i in range(1)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
# make initial conditions
self.reset_world(world)
return world
def reset_world(self, world):
world = World()
# add agents
world.agents = [
Agent(i, self.num_tasks, self.maxTask, self.num_agents)
for i in range(self.num_agents)
]
world.int_matrix = self.generate_graph(world)
for i, agent in enumerate(world.agents):
_, agent.state[0], agent.nghd = self.secondhop(world.int_matrix, i)
agent.c = np.random.uniform(0, 100, self.num_tasks)
world.initializeCommDictionaries()
world.updateCommNeighbors()
reward_i = self.ideal_reward(world)
return reward_i
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 10
# add agents
world.agents = [Agent() for i in range(2)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
# add landmarks
world.landmarks = [Landmark() for i in range(3)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
# make initial conditions
self.reset_world(world)
return world
def make_world(self,
name,
num_good_agents=0,
num_adversaries=0,
is_random_states_for_new_agent=False,
bounds=False,
REWARD_FOR_COLISION=10,
adv_speed=1.5,
good_speed=0.7):
self.name = name
self.bounds = bounds
self.is_random_states_for_new_agent = is_random_states_for_new_agent
self.REWARD_FOR_COLISION = REWARD_FOR_COLISION
self.evaluate = False
world = World()
# set any world properties first
world.dim_c = 2
num_good_agents = num_good_agents
num_adversaries = num_adversaries
num_agents = num_adversaries + num_good_agents
num_landmarks = 0
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.02 if agent.adversary else 0.02
agent.accel = 3.0 if agent.adversary else 4.0
# agent.accel = 20.0 if agent.adversary else 25.0
agent.max_speed = adv_speed if agent.adversary else good_speed
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.2
landmark.boundary = False
# make initial conditions
self.reset_world(world)
self.evaluate = False
return world
def make_world(self):
"""Define two agents, one box, and two targets.
Note that world.goals are used only for hierarchical RL visualization only
Note that this domain should have one target.
But, we empirically found that having the additional right target does not affect
performance much as the reward is based on the left target only
"""
world = World()
world.agents = [Agent() for i in range(2)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.size = 0.1 # Radius
self.boxes = [Landmark() for _ in range(1)]
for i, box in enumerate(self.boxes):
box.name = 'box %d' % i
box.collide = True
box.movable = True
box.size = 0.25
box.initial_mass = 7.
box.index = i
world.landmarks.append(box)
self.targets = [Landmark() for _ in range(2)]
for i, target in enumerate(self.targets):
target.name = 'target %d' % i
target.collide = False
target.movable = False
target.size = 0.05
target.index = i
world.landmarks.append(target)
world.goals = [Goal() for i in range(len(world.agents))]
for i, goal in enumerate(world.goals):
goal.name = 'goal %d' % i
goal.collide = False
goal.movable = False
self.reset_world(world)
return world
def make_world(self, args):
if ('boundary' in args.keys()) and args['boundary']:
world = World(boundary=args['boundary'])
else:
world = World()
# set any world properties first
world.dim_c = 2
if ('num_agents' in args.keys()) and args['num_agents']:
num_good_agents = args['num_agents']
else:
num_good_agents = 2
if ('num_adversaries' in args.keys()) and args['num_adversaries']:
num_adversaries = args['num_adversaries']
else:
num_adversaries = 1
num_agents = num_adversaries + num_good_agents
world.num_agents = num_agents
if ('num_landmarks' in args.keys()) and args['num_landmarks']:
num_landmarks = args['num_landmarks']
else:
num_landmarks = 2
# num_agents = 3
# world.num_agents = num_agents
# num_adversaries = 1
# num_landmarks = num_agents - 1
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = False
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.15
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
landmark.size = 0.08
# make initial conditions
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_agents = 6
world.num_agents = num_agents
num_adversaries = num_agents - 1
num_landmarks = 1
num_obstacles = 1
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.08 if i < num_adversaries else 0.10
agent.max_speed = 0.9 if i < num_adversaries else None
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = False
landmark.movable = False
landmark.size = 0.03
# add obstacle
world.obstacles = [Landmark() for i in range(num_obstacles)]
for i, obstacle in enumerate(world.obstacles):
obstacle.name = 'obstacle %d' % i
obstacle.collide = True
obstacle.movable = True
obstacle.size = 0.30
# make initial conditions
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 obstacle in world.obstacles:
obstacle.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
self.obstacle_vel = np.random.uniform(-1, +1, world.dim_p)
obstacle.state.p_vel = self.obstacle_vel
obstacle.state.c = np.zeros(world.dim_c)
self.reset_world(world)
return world
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_agents = 1
num_obstacle = 4
num_target = 1
world.collaborative = True
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.size = 0.1
# add obstacles
world.landmarks = [Landmark() for i in range(num_obstacle)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'obstacle %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.1
# add target
target = Landmark()
target.name = 'target'
target.collide = False
target.movable = False
target.size = 0.1
# Merge the landmarks (obstacles + target)
world.landmarks.append(target)
# make initial conditions
self.n = num_agents
self.x = [0.0, 0.0] * num_agents
self.y = [0.0, 0.0] * num_agents
self.theta = [0.0, 0.0] * num_agents
self.reset_world(world)
# Send initial information to pheromone system
self.sock_sender.send_number(self.n)
return world