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()