ant_env.py 文件源码

def step(self, action):
        self.forward_dynamics(action)
        comvel = self.get_body_comvel("torso")
        forward_reward = comvel[0]
        lb, ub = self.action_bounds
        scaling = (ub - lb) * 0.5
        ctrl_cost = 0.5 * 1e-2 * np.sum(np.square(action / scaling))
        contact_cost = 0.5 * 1e-3 * np.sum(
            np.square(np.clip(self.model.data.cfrc_ext, -1, 1))),
        survive_reward = 0.05
        reward = forward_reward - ctrl_cost - contact_cost + survive_reward
        state = self._state
        notdone = np.isfinite(state).all() \
            and state[2] >= 0.2 and state[2] <= 1.0
        done = not notdone
        ob = self.get_current_obs()
        return Step(ob, float(reward), done)