#include <mlpack/core.hpp>#include <mlpack/methods/ann/ffn.hpp>#include <mlpack/methods/ann/init_rules/gaussian_init.hpp>#include <mlpack/methods/ann/layer/layer.hpp>#include <mlpack/methods/ann/loss_functions/mean_squared_error.hpp>#include <mlpack/methods/ann/loss_functions/empty_loss.hpp>#include <mlpack/methods/reinforcement_learning/q_learning.hpp>#include <mlpack/methods/reinforcement_learning/sac.hpp>#include <mlpack/methods/reinforcement_learning/q_networks/simple_dqn.hpp>#include <mlpack/methods/reinforcement_learning/q_networks/dueling_dqn.hpp>#include <mlpack/methods/reinforcement_learning/q_networks/categorical_dqn.hpp>#include <mlpack/methods/reinforcement_learning/environment/env_type.hpp>#include <mlpack/methods/reinforcement_learning/environment/pendulum.hpp>#include <mlpack/methods/reinforcement_learning/environment/mountain_car.hpp>#include <mlpack/methods/reinforcement_learning/environment/acrobot.hpp>#include <mlpack/methods/reinforcement_learning/environment/cart_pole.hpp>#include <mlpack/methods/reinforcement_learning/environment/double_pole_cart.hpp>#include <mlpack/methods/reinforcement_learning/policy/greedy_policy.hpp>#include <mlpack/methods/reinforcement_learning/training_config.hpp>#include <ensmallen.hpp>#include <numeric>#include "catch.hpp"
Include dependency graph for q_learning_test.cpp:
Functions | |
| template<typename AgentType > | |
| bool | testAgent (AgentType &agent, const double rewardThreshold, const size_t noOfEpisodes, const size_t consecutiveEpisodesTest=50) |
| TEST_CASE ("CartPoleWithDQN", "[QLearningTest]") | |
| Test DQN in Cart Pole task. | |
| TEST_CASE ("CartPoleWithDQNPrioritizedReplay", "[QLearningTest]") | |
| Test DQN in Cart Pole task with Prioritized Replay. | |
| TEST_CASE ("CartPoleWithDoubleDQN", "[QLearningTest]") | |
| Test Double DQN in Cart Pole task. | |
| TEST_CASE ("AcrobotWithDQN", "[QLearningTest]") | |
| Test DQN in Acrobot task. | |
| TEST_CASE ("MountainCarWithDQN", "[QLearningTest]") | |
| Test DQN in Mountain Car task. | |
| TEST_CASE ("DoublePoleCartWithDQN", "[QLearningTest]") | |
| Test DQN in DoublePoleCart task. | |
| TEST_CASE ("CartPoleWithDuelingDQN", "[QLearningTest]") | |
| Test Dueling DQN in Cart Pole task. | |
| TEST_CASE ("CartPoleWithDuelingDQNPrioritizedReplay", "[QLearningTest]") | |
| Test Dueling DQN in Cart Pole task with Prioritized Replay. | |
| TEST_CASE ("CartPoleWithNoisyDQN", "[QLearningTest]") | |
| Test Noisy DQN in Cart Pole task. | |
| TEST_CASE ("CartPoleWithDuelingDoubleNoisyDQN", "[QLearningTest]") | |
| Test Dueling-Double-Noisy DQN in Cart Pole task. | |
| TEST_CASE ("CartPoleWithNStepDQN", "[QLearningTest]") | |
| Test N-step DQN in Cart Pole task. More... | |
| TEST_CASE ("CartPoleWithNStepPrioritizedDQN", "[QLearningTest]") | |
| Test N-step Prioritized DQN in Cart Pole task. More... | |
| TEST_CASE ("CartPoleWithCategoricalDQN", "[QLearningTest]") | |
| Test Categorical DQN in Cart Pole task. | |
| TEST_CASE ("PendulumWithSAC", "[QLearningTest]") | |
| Test SAC on Pendulum task. | |
| TEST_CASE ("SACForMultipleActions", "[QLearningTest]") | |
| A test to ensure SAC works with multiple actions in action space. | |
Detailed Description
Test for Q-Learning implementation
mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.
Function Documentation
◆ TEST_CASE() [1/2]
| TEST_CASE | ( | "CartPoleWithNStepDQN" | , |
| "" | [QLearningTest] | ||
| ) |
Test N-step DQN in Cart Pole task.
For N-step learning, we need to specify n as the last parameter in the replay method. Here we use n = 3.
◆ TEST_CASE() [2/2]
| TEST_CASE | ( | "CartPoleWithNStepPrioritizedDQN" | , |
| "" | [QLearningTest] | ||
| ) |
Test N-step Prioritized DQN in Cart Pole task.
For N-step learning, we need to specify n as the last parameter in the replay method. Here we use n = 3.
