Reinforcement Learning, Gaming, Deep Learning.
0.418, 100) ang_vel = np.random.random(size=(10000, 1)) * 0.1 g1, g2 = np.meshgrid(pos, ang) grid = np.stack((g1,g2), axis=-1) grid = grid.reshape(-1, 2) grid = np.hstack((grid, vel, ang_vel)) grid = torch.from_numpy(grid).float() loc, _ = policy(grid) plot_vals = loc.numpy() plot_vals =