Python mujoco_env.MujocoEnv方法代码示例

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(
        self,
        direction=1,
        maze_length=0.6,
        sparse_reward=False,
        no_reward=False,
        include_vel=False,
        episode_length=100,
    ):
        utils.EzPickle.__init__(self)
        self.sparse_reward = sparse_reward
        self.no_reward = no_reward
        self.include_vel = include_vel
        self.max_episode_length = episode_length
        self.direction = direction
        self.length = maze_length

        self.episode_length = 0

        model = point_mass_maze(direction=self.direction, length=self.length)
        with model.asfile() as f:
            mujoco_env.MujocoEnv.__init__(self, f.name, 5) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self, direction=1, maze_length=0.6,
                 sparse_reward=False, no_reward=False, episode_length=100, grayscale=True,
                 width=64, height=64):
        utils.EzPickle.__init__(self)
        self.sparse_reward = sparse_reward
        self.no_reward = no_reward
        self.max_episode_length = episode_length
        self.direction = direction
        self.length = maze_length

        self.width = width
        self.height = height
        self.grayscale=grayscale

        self.episode_length = 0

        model = point_mass_maze(direction=self.direction, length=self.length, borders=False)
        with model.asfile() as f:
            mujoco_env.MujocoEnv.__init__(self, f.name, 5)

        if self.grayscale:
            self.observation_space = Box(0, 1, shape=(width, height))
        else:
            self.observation_space = Box(0, 1, shape=(width, height, 3)) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        utils.EzPickle.__init__(self)
        mujoco_env.MujocoEnv.__init__(self, 'reacher.xml', 2)

    # def _step(self, a):
    #     # x = self._get_obs()[None]
    #     # assert np.allclose(self.get_body_com("fingertip")[:2], get_fingertips(x)),\
    #     # str(self.get_body_com("fingertip")) + " "+ str(get_fingertips(x))
    #     vec = self.get_body_com("fingertip")-self.get_body_com("target")
    #     reward_dist = - np.linalg.norm(vec[:2])
    #     reward_ctrl = - np.square(a).sum()*0.01
    #     reward = reward_dist + reward_ctrl
    #     self.do_simulation(a, self.frame_skip)
    #     ob = self._get_obs()
    #     done = False
    #     return ob, reward, done, dict(reward_dist=reward_dist, reward_ctrl=reward_ctrl) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self, CentipedeLegNum=4, is_crippled=False):

        # get the path of the environments
        if is_crippled:
            xml_name = 'CpCentipede' + self.get_env_num_str(CentipedeLegNum) + \
                '.xml'
        else:
            xml_name = 'Centipede' + self.get_env_num_str(CentipedeLegNum) + \
                '.xml'
        xml_path = os.path.join(init_path.get_base_dir(),
                                'environments', 'assets',
                                xml_name)
        xml_path = str(os.path.abspath(xml_path))
        self.num_body = int(np.ceil(CentipedeLegNum / 2.0))
        self._control_cost_coeff = .5 * 4 / CentipedeLegNum
        self._contact_cost_coeff = 0.5 * 1e-3 * 4 / CentipedeLegNum

        self.torso_geom_id = 1 + np.array(range(self.num_body)) * 5
        # make sure the centipede is not born to be end of episode
        self.body_qpos_id = 6 + 6 + np.array(range(self.num_body)) * 6
        self.body_qpos_id[-1] = 5

        mujoco_env.MujocoEnv.__init__(self, xml_path, 5)

        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self, pod_number=3, is_crippled=False):

        # get the path of the environments
        if is_crippled:
            xml_name = 'CrippledSnake' + self.get_env_num_str(pod_number) + \
                '.xml'
        else:
            xml_name = 'Snake' + self.get_env_num_str(pod_number) + '.xml'
        xml_path = os.path.join(os.path.join(init_path.get_base_dir(),
                                'environments', 'assets', xml_name))
        xml_path = str(os.path.abspath(xml_path))
        self.num_body = pod_number
        self._direction = 0
        self.ctrl_cost_coeff = 0.0001 / pod_number * 3

        mujoco_env.MujocoEnv.__init__(self, xml_path, 4)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self, pod_number=2):

        # get the path of the environments
        xml_name = 'Reacher' + self.get_env_num_str(pod_number) + '.xml'
        xml_path = os.path.join(os.path.join(init_path.get_base_dir(),
                                'environments', 'assets', xml_name))
        xml_path = str(os.path.abspath(xml_path))

        # the environment coeff
        self.num_body = pod_number + 1
        self._task_indicator = -1.0

        self._ctrl_coeff = 2.0 / (self.num_body / 2 + 1)
        # norm the max penalty to be 1, max norm is self.num_body * 0.1 * 2
        self._dist_coeff = 2.0 / self.num_body

        mujoco_env.MujocoEnv.__init__(self, xml_path, 2)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self,
                 xml_file='swimmer.xml',
                 forward_reward_weight=1.0,
                 ctrl_cost_weight=1e-4,
                 reset_noise_scale=0.1,
                 exclude_current_positions_from_observation=True):
        utils.EzPickle.__init__(**locals())

        self._forward_reward_weight = forward_reward_weight
        self._ctrl_cost_weight = ctrl_cost_weight

        self._reset_noise_scale = reset_noise_scale

        self._exclude_current_positions_from_observation = (
            exclude_current_positions_from_observation)

        mujoco_env.MujocoEnv.__init__(self, xml_file, 4) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        mujoco_env.MujocoEnv.__init__(self, 'half_cheetah.xml', 1)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        mujoco_env.MujocoEnv.__init__(self, 'half_cheetah.xml', 5)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self, max_timesteps=1000, disabled=False, gear=150):
        self.timesteps = 0
        self.max_timesteps = max_timesteps

        if disabled:
            model = angry_ant_crippled(gear=gear)
        else:
            model = ant_env(gear=gear)

        with model.asfile() as f:
            mujoco_env.MujocoEnv.__init__(self, f.name, 5) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self, sparse_reward=False, no_reward=False, episode_length=200):
        utils.EzPickle.__init__(self)
        self.sparse_reward = sparse_reward
        self.no_reward = no_reward
        self.max_episode_length = episode_length
        self.goal_pos = np.asarray([0.0, 0.0])

        self.episode_length = 0

        model = pusher(goal_pos=[self.goal_pos[0], self.goal_pos[1], -0.323])
        with model.asfile() as f:
            mujoco_env.MujocoEnv.__init__(self, f.name, 5) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        mujoco_env.MujocoEnv.__init__(self, 'inverted_double_pendulum.xml', 5)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        mujoco_env.MujocoEnv.__init__(self, 'humanoidstandup.xml', 5)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        mujoco_env.MujocoEnv.__init__(self, 'ant.xml', 5)
        utils.EzPickle.__init__(self) 

# 需要导入模块: from gym.envs.mujoco import mujoco_env [as 别名]
# 或者: from gym.envs.mujoco.mujoco_env import MujocoEnv [as 别名]
def __init__(self):
        utils.EzPickle.__init__(self)
        mujoco_env.MujocoEnv.__init__(self, 'pusher.xml', 5)