from mountaincar import MountainCar from gp_gym_info import info import gym # GP Parameters info["env_name"] = "MountainCar-v0" info["pop_size"] = 100 info["max_gens"] = 10 info["max_depth"] = 1 info["num_eps"] = 100 agent = MountainCar(info) best_program = agent.train() print(best_program) f = agent.fit(best_program, 100, 200, render=False) print(f)
info["env_name"] = "MountainCarContinuous-v0" info["pop_size"] = 100 info["max_gens"] = 10 info["max_depth"] = 1 info["tournament_size"] = 5 info["num_eps"] = 10 agent = MountainCar(info) solutions = {} force_values = np.arange(0.0, 1.0, 0.1) fitness_scores = [] counter = 1 for force in force_values: solution = "IFLTE(0.0, velocity, {}, {})".format(force, -force) f = agent.fit(solution, 100, 200, render=False)[0] fitness_scores.append(f) # Timing print(counter) counter += 1 if f >= 90: solutions[solution] = f # Print solutions and their fitness scores print() for s, f in solutions.items(): print("{}: {}".format(s, f)) # Plot fitness scores