def run_forward_model(config, i):
env = gym.make('HalfCheetahBulletEnv-v0')
state_dim = env.observation_space.shape[0]
action_dim = env.action_space.shape[0]
experiment = ExperimentDDPG('HalfCheetahBulletEnv-v0', env, config)
agent = DDPGBulletForwardModelAgent(state_dim, action_dim, config)
experiment.run_forward_model(agent, i)
env.close()
def run_forward_model(env_name, config, trial):
env = create_env(env_name)
state_dim = env.observation_space.shape
action_dim = env.action_space.shape[0]
experiment = ExperimentDDPG(env_name, env, config)
agent = DDPGAerisForwardModelAgent(state_dim, action_dim, config)
experiment.run_forward_model(agent, trial)
env.close()