def main(parser):
mode = parser._mode
args = parser.args
env = MultiAnt(n_legs=args.n_legs,
ts=args.ts,
integrator=args.integrator,
leg_length=args.leg_length,
out_file=args.out_file,
base_file=args.base_file,
reward_mech=args.reward_mech)
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
if args.curriculum:
curr = Curriculum(args.curriculum)
run(curr)
else:
run()
def main(parser):
mode = parser._mode
args = parser.args
env_config = dict(n_walkers=args.n_walkers,
position_noise=args.position_noise,
angle_noise=args.angle_noise,
reward_mech=args.reward_mech,
forward_reward=args.forward_reward,
fall_reward=args.fall_reward,
drop_reward=args.drop_reward,
terminate_on_fall=bool(args.terminate_on_fall),
one_hot=bool(args.one_hot))
env = MultiWalkerEnv(**env_config)
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
if args.curriculum:
curr = Curriculum(args.curriculum)
run(curr)
else:
run()
def main(parser):
mode = parser._mode
args = parser.args
env = MAWaterWorld(args.n_pursuers,
args.n_evaders,
args.n_coop,
args.n_poison,
radius=args.radius,
n_sensors=args.n_sensors,
food_reward=args.food_reward,
poison_reward=args.poison_reward,
encounter_reward=args.encounter_reward,
reward_mech=args.reward_mech,
sensor_range=args.sensor_range,
obstacle_loc=None,
addid=True if not args.noid else False,
speed_features=bool(args.speed_features))
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
if args.curriculum:
curr = Curriculum(args.curriculum)
run(curr)
else:
run()
def main(parser):
mode = parser._mode
args = parser.args
env_config = dict(n_agents=args.n_agents,
speed_noise=args.speed_noise,
position_noise=args.position_noise,
angle_noise=args.angle_noise,
reward_mech=args.reward_mech,
rew_arrival=args.rew_arrival,
rew_closing=args.rew_closing,
rew_nmac=args.rew_nmac,
rew_large_turnrate=args.rew_large_turnrate,
rew_large_acc=args.rew_large_acc,
pen_action_heavy=args.pen_action_heavy,
one_hot=bool(args.one_hot))
env = MultiAircraftEnv(**env_config)
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
if args.curriculum:
curr = Curriculum(args.curriculum)
run(curr)
else:
run()
def main(parser):
mode = parser._mode
args = parser.args
if args.map_file:
map_pool = np.load(args.map_file)
else:
if args.map_type == 'rectangle':
env_map = TwoDMaps.rectangle_map(
*map(int, args.map_size.split(',')))
elif args.map_type == 'complex':
env_map = TwoDMaps.complex_map(*map(int, args.map_size.split(',')))
else:
raise NotImplementedError()
map_pool = [env_map]
env = PursuitEvade(map_pool,
n_evaders=args.n_evaders,
n_pursuers=args.n_pursuers,
obs_range=args.obs_range,
n_catch=args.n_catch,
urgency_reward=args.urgency,
surround=bool(args.surround),
sample_maps=bool(args.sample_maps),
flatten=bool(args.flatten),
reward_mech=args.reward_mech,
catchr=args.catchr,
term_pursuit=args.term_pursuit,
include_id=not bool(args.noid))
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
run()
def main(parser):
mode = parser._mode
args = parser.args
if args.map_file:
map_pool = np.load(args.map_file)
else:
if args.map_type == 'rectangle':
#passes in tuple of what map should be
env_map = TwoDMaps.rectangle_map(*map(int, args.map_size.split(',')))
elif args.map_type == 'complex':
env_map = TwoDMaps.complex_map(*map(int, args.map_size.split(',')))
else:
raise NotImplementedError()
#map pool is list of maps of different shapes for environment
map_pool = [env_map]
env = sniper(map_pool, n_targets=args.n_targets, n_snipers=args.n_snipers,
obs_range=args.obs_range, n_catch=args.n_catch,
urgency_reward=args.urgency,
surround=bool(args.surround), sample_maps=bool(args.sample_maps),
flatten=bool(args.flatten),
reward_mech=args.reward_mech,
catchr=args.catchr,
term_sniper=args.term_sniper)
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
run()
def main(parser):
mode = parser._mode
args = parser.args
env = ContinuousHostageWorld(
n_good=args.n_good,
n_hostages=args.n_hostages,
n_bad=args.n_bad,
n_coop_save=args.n_coop_save,
n_coop_avoid=args.n_coop_avoid,
radius=args.radius,
key_loc=args.key_loc,
bad_speed=args.bad_speed,
n_sensors=args.n_sensors,
sensor_range=args.sensor_range,
save_reward=args.save_reward,
hit_reward=args.hit_reward,
encounter_reward=args.encounter_reward,
bomb_reward=args.bomb_reward,
bomb_radius=args.bomb_radius,
control_penalty=args.control_penalty,
reward_mech=args.reward_mech,
)
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
elif mode == 'rltools':
from runners.rurltools import RLToolsRunner
run = RLToolsRunner(env, args)
else:
raise NotImplementedError()
run()
def main(parser):
mode = parser._mode
args = parser.args
env = MAContWorld(args.n_rovers, args.n_areas_of_int, args.n_coop, args.n_crater,
radius=args.radius, n_sensors=args.n_sensors, scout_reward=args.scout_reward,
crater_reward=args.crater_reward, encounter_reward=args.encounter_reward,
reward_mech=args.reward_mech, sensor_range=args.sensor_range,
obstacle_loc=None, addid=True if not args.noid else False,
speed_features=bool(args.speed_features))
if args.buffer_size > 1:
env = ObservationBuffer(env, args.buffer_size)
if mode == 'rllab':
from runners.rurllab import RLLabRunner
run = RLLabRunner(env, args)
else:
raise NotImplementedError()
if args.curriculum:
curr = Curriculum(args.curriculum)
run(curr)
else:
run()