# print expanded # policy search x = goal[0] y = goal[1] policy[x][y] = '*' path = [] path.append([x, y]) while ([x, y] != init): x1 = x - delta[action[x][y]][0] y1 = y - delta[action[x][y]][1] policy[x1][y1] = delta_name[action[x][y]] x = x1 y = y1 path.append([x, y]) # print policy path.reverse() # print path smooth_path = gridworld.smooth_path(path) gridworld.draw_path(smooth_path) gridworld.show() return smooth_path smooth_path = run_a_star(grid, heuristics, init, goal, cost=1) for point in smooth_path: gridworld.draw_shape("circle", point, 8) gridworld.show() time.sleep(1) gridworld.loop()