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| import numpy as np | |
| from gym import utils | |
| from gym.envs.mujoco import mujoco_env | |
| from jinja2 import Template | |
| import os | |
| class ManyAgentAntEnv(mujoco_env.MujocoEnv, utils.EzPickle): | |
| def __init__(self, **kwargs): | |
| agent_conf = kwargs.get("agent_conf") | |
| n_agents = int(agent_conf.split("x")[0]) | |
| n_segs_per_agents = int(agent_conf.split("x")[1]) | |
| n_segs = n_agents * n_segs_per_agents | |
| # Check whether asset file exists already, otherwise create it | |
| asset_path = os.path.join( | |
| os.path.dirname(os.path.abspath(__file__)), 'assets', | |
| 'manyagent_ant_{}_agents_each_{}_segments.auto.xml'.format(n_agents, n_segs_per_agents) | |
| ) | |
| #if not os.path.exists(asset_path): | |
| print("Auto-Generating Manyagent Ant asset with {} segments at {}.".format(n_segs, asset_path)) | |
| self._generate_asset(n_segs=n_segs, asset_path=asset_path) | |
| #asset_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'assets',git p | |
| # 'manyagent_swimmer.xml') | |
| mujoco_env.MujocoEnv.__init__(self, asset_path, 4) | |
| utils.EzPickle.__init__(self) | |
| def _generate_asset(self, n_segs, asset_path): | |
| template_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'assets', 'manyagent_ant.xml.template') | |
| with open(template_path, "r") as f: | |
| t = Template(f.read()) | |
| body_str_template = """ | |
| <body name="torso_{:d}" pos="-1 0 0"> | |
| <!--<joint axis="0 1 0" name="nnn_{:d}" pos="0.0 0.0 0.0" range="-1 1" type="hinge"/>--> | |
| <geom density="100" fromto="1 0 0 0 0 0" size="0.1" type="capsule"/> | |
| <body name="front_right_leg_{:d}" pos="0 0 0"> | |
| <geom fromto="0.0 0.0 0.0 0.0 0.2 0.0" name="aux1_geom_{:d}" size="0.08" type="capsule"/> | |
| <body name="aux_2_{:d}" pos="0.0 0.2 0"> | |
| <joint axis="0 0 1" name="hip1_{:d}" pos="0.0 0.0 0.0" range="-30 30" type="hinge"/> | |
| <geom fromto="0.0 0.0 0.0 -0.2 0.2 0.0" name="right_leg_geom_{:d}" size="0.08" type="capsule"/> | |
| <body pos="-0.2 0.2 0"> | |
| <joint axis="1 1 0" name="ankle1_{:d}" pos="0.0 0.0 0.0" range="-70 -30" type="hinge"/> | |
| <geom fromto="0.0 0.0 0.0 -0.4 0.4 0.0" name="right_ankle_geom_{:d}" size="0.08" type="capsule"/> | |
| </body> | |
| </body> | |
| </body> | |
| <body name="back_leg_{:d}" pos="0 0 0"> | |
| <geom fromto="0.0 0.0 0.0 0.0 -0.2 0.0" name="aux2_geom_{:d}" size="0.08" type="capsule"/> | |
| <body name="aux2_{:d}" pos="0.0 -0.2 0"> | |
| <joint axis="0 0 1" name="hip2_{:d}" pos="0.0 0.0 0.0" range="-30 30" type="hinge"/> | |
| <geom fromto="0.0 0.0 0.0 -0.2 -0.2 0.0" name="back_leg_geom_{:d}" size="0.08" type="capsule"/> | |
| <body pos="-0.2 -0.2 0"> | |
| <joint axis="-1 1 0" name="ankle2_{:d}" pos="0.0 0.0 0.0" range="-70 -30" type="hinge"/> | |
| <geom fromto="0.0 0.0 0.0 -0.4 -0.4 0.0" name="third_ankle_geom_{:d}" size="0.08" type="capsule"/> | |
| </body> | |
| </body> | |
| </body> | |
| """ | |
| body_close_str_template = "</body>\n" | |
| actuator_str_template = """\t <motor ctrllimited="true" ctrlrange="-1.0 1.0" joint="hip1_{:d}" gear="150"/> | |
| <motor ctrllimited="true" ctrlrange="-1.0 1.0" joint="ankle1_{:d}" gear="150"/> | |
| <motor ctrllimited="true" ctrlrange="-1.0 1.0" joint="hip2_{:d}" gear="150"/> | |
| <motor ctrllimited="true" ctrlrange="-1.0 1.0" joint="ankle2_{:d}" gear="150"/>\n""" | |
| body_str = "" | |
| for i in range(1, n_segs): | |
| body_str += body_str_template.format(*([i] * 16)) | |
| body_str += body_close_str_template * (n_segs - 1) | |
| actuator_str = "" | |
| for i in range(n_segs): | |
| actuator_str += actuator_str_template.format(*([i] * 8)) | |
| rt = t.render(body=body_str, actuators=actuator_str) | |
| with open(asset_path, "w") as f: | |
| f.write(rt) | |
| pass | |
| def step(self, a): | |
| xposbefore = self.get_body_com("torso_0")[0] | |
| self.do_simulation(a, self.frame_skip) | |
| xposafter = self.get_body_com("torso_0")[0] | |
| forward_reward = (xposafter - xposbefore) / self.dt | |
| ctrl_cost = .5 * np.square(a).sum() | |
| contact_cost = 0.5 * 1e-3 * np.sum(np.square(np.clip(self.sim.data.cfrc_ext, -1, 1))) | |
| survive_reward = 1.0 | |
| reward = forward_reward - ctrl_cost - contact_cost + survive_reward | |
| state = self.state_vector() | |
| notdone = np.isfinite(state).all() \ | |
| and state[2] >= 0.2 and state[2] <= 1.0 | |
| done = not notdone | |
| ob = self._get_obs() | |
| return ob, reward, done, dict( | |
| reward_forward=forward_reward, | |
| reward_ctrl=-ctrl_cost, | |
| reward_contact=-contact_cost, | |
| reward_survive=survive_reward | |
| ) | |
| def _get_obs(self): | |
| return np.concatenate( | |
| [ | |
| self.sim.data.qpos.flat[2:], | |
| self.sim.data.qvel.flat, | |
| np.clip(self.sim.data.cfrc_ext, -1, 1).flat, | |
| ] | |
| ) | |
| def reset_model(self): | |
| qpos = self.init_qpos + self.np_random.uniform(size=self.model.nq, low=-.1, high=.1) | |
| qvel = self.init_qvel + self.np_random.randn(self.model.nv) * .1 | |
| self.set_state(qpos, qvel) | |
| return self._get_obs() | |
| def viewer_setup(self): | |
| self.viewer.cam.distance = self.model.stat.extent * 0.5 | |