| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| from ddpg import DDPG |
| from rllab.envs.box2d.cartpole_env import CartpoleEnv |
| from rllab.envs.normalized_env import normalize |
| from policies import DeterministicMLPPolicy |
| from qfuncs import ContinuousMLPQ |
| from strategies import OUStrategy |
| from utils import SEED |
| import mxnet as mx |
| |
| # set environment, policy, qfunc, strategy |
| |
| env = normalize(CartpoleEnv()) |
| |
| policy = DeterministicMLPPolicy(env.spec) |
| qfunc = ContinuousMLPQ(env.spec) |
| strategy = OUStrategy(env.spec) |
| |
| # set the training algorithm and train |
| |
| algo = DDPG( |
| env=env, |
| policy=policy, |
| qfunc=qfunc, |
| strategy=strategy, |
| ctx=mx.gpu(0), |
| max_path_length=100, |
| epoch_length=1000, |
| memory_start_size=10000, |
| n_epochs=1000, |
| discount=0.99, |
| qfunc_lr=1e-3, |
| policy_lr=1e-4, |
| seed=SEED) |
| |
| algo.train() |
