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Merge pull request #2014 from zoq/DoublePoleCartWithDQNFix

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Fix occasional `QLearningTest/DoublePoleCartWithDQN` failure.
This commit is contained in:
Marcus Edel
2019-09-17 12:18:03 +02:00
committed by GitHub
parent aeff773f35 1114937fd1
commit 2e2e0f59cd
1 changed files with 14 additions and 18 deletions
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src/mlpack/tests/q_learning_test.cpp
+14 -18
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@@ -400,25 +400,23 @@ BOOST_AUTO_TEST_CASE(MountainCarWithDQN)
//! Test DQN in DoublePoleCart task.
BOOST_AUTO_TEST_CASE(DoublePoleCartWithDQN)
{
// We will allow three trials total.
// We will allow four trials total.
bool success = false;
for (size_t trial = 0; trial < 3; trial++)
for (size_t trial = 0; trial < 4; trial++)
{
// Set up the network.
FFN<MeanSquaredError<>, GaussianInitialization> model(MeanSquaredError<>(),
GaussianInitialization(0, 0.001));
model.Add<Linear<>>(6, 128);
model.Add<Linear<>>(6, 256);
model.Add<ReLULayer<>>();
model.Add<Linear<>>(128, 32);
model.Add<ReLULayer<>>();
model.Add<Linear<>>(32, 3);
model.Add<Linear<>>(256, 3);
// Set up the policy and replay method.
GreedyPolicy<DoublePoleCart> policy(1.0, 1000, 0.1, 0.99);
RandomReplay<DoublePoleCart> replayMethod(20, 10000);
TrainingConfig config;
config.StepSize() = 0.001;
config.StepSize() = 0.01;
config.Discount() = 0.9;
config.TargetNetworkSyncInterval() = 100;
config.ExplorationSteps() = 100;
@@ -432,27 +430,25 @@ BOOST_AUTO_TEST_CASE(DoublePoleCartWithDQN)
size_t episodes = 0;
bool converged = true;
size_t successive = 0;
size_t episodeSuccesses = 0;
while (true)
{
double episodeReturn = agent.Episode();
episodes += 1;
if (episodes > 1000)
if (episodeReturn >= 280)
episodeSuccesses++;
if (episodes > 2000)
{
Log::Debug << "Multiple Pole Cart with DQN failed." << std::endl;
Log::Debug << "Cart Pole with DQN failed." << std::endl;
converged = false;
break;
}
if (episodeReturn >= 380)
successive++;
else if (successive)
successive = 0;
// If the model can solve the environment in two consecutive trials this
// is fine for a simple test.
if (successive >= 2)
// If the model can solve the environment in two trials this is fine for
// a simple test.
if (episodeSuccesses >= 2)
{
Log::Debug << "QLearning has succeeded in the multiple pole cart" <<
" environment." << std::endl;