mlpack  3.0.3
mlpack::rl Namespace Reference

Classes

class  Acrobat
 Implementation of Acrobat game. More...

 
class  AggregatedPolicy
 
class  AsyncLearning
 Wrapper of various asynchronous learning algorithms, e.g. More...

 
class  CartPole
 Implementation of Cart Pole task. More...

 
class  ContinuousMountainCar
 Implementation of Continuous Mountain Car task. More...

 
class  GreedyPolicy
 Implementation for epsilon greedy policy. More...

 
class  MountainCar
 Implementation of Mountain Car task. More...

 
class  NStepQLearningWorker
 Forward declaration of NStepQLearningWorker. More...

 
class  OneStepQLearningWorker
 Forward declaration of OneStepQLearningWorker. More...

 
class  OneStepSarsaWorker
 Forward declaration of OneStepSarsaWorker. More...

 
class  Pendulum
 Implementation of Pendulum task. More...

 
class  QLearning
 Implementation of various Q-Learning algorithms, such as DQN, double DQN. More...

 
class  RandomReplay
 Implementation of random experience replay. More...

 
class  TrainingConfig
 

Typedefs

template
<
typename
EnvironmentType
,
typename
NetworkType
,
typename
UpdaterType
,
typename
PolicyType
>
using NStepQLearning = AsyncLearning< NStepQLearningWorker< EnvironmentType, NetworkType, UpdaterType, PolicyType >, EnvironmentType, NetworkType, UpdaterType, PolicyType >
 Convenient typedef for async n step q-learning. More...

 
template
<
typename
EnvironmentType
,
typename
NetworkType
,
typename
UpdaterType
,
typename
PolicyType
>
using OneStepQLearning = AsyncLearning< OneStepQLearningWorker< EnvironmentType, NetworkType, UpdaterType, PolicyType >, EnvironmentType, NetworkType, UpdaterType, PolicyType >
 Convenient typedef for async one step q-learning. More...

 
template
<
typename
EnvironmentType
,
typename
NetworkType
,
typename
UpdaterType
,
typename
PolicyType
>
using OneStepSarsa = AsyncLearning< OneStepSarsaWorker< EnvironmentType, NetworkType, UpdaterType, PolicyType >, EnvironmentType, NetworkType, UpdaterType, PolicyType >
 Convenient typedef for async one step Sarsa. More...

 

Typedef Documentation

◆ NStepQLearning

using NStepQLearning = AsyncLearning<NStepQLearningWorker<EnvironmentType, NetworkType, UpdaterType, PolicyType>, EnvironmentType, NetworkType, UpdaterType, PolicyType>

Convenient typedef for async n step q-learning.

Template Parameters
EnvironmentTypeThe type of the reinforcement learning task.
NetworkTypeThe type of the network model.
UpdaterTypeThe type of the optimizer.
PolicyTypeThe type of the behavior policy.

Definition at line 233 of file async_learning.hpp.

◆ OneStepQLearning

using OneStepQLearning = AsyncLearning<OneStepQLearningWorker<EnvironmentType, NetworkType, UpdaterType, PolicyType>, EnvironmentType, NetworkType, UpdaterType, PolicyType>

Convenient typedef for async one step q-learning.

Template Parameters
EnvironmentTypeThe type of the reinforcement learning task.
NetworkTypeThe type of the network model.
UpdaterTypeThe type of the optimizer.
PolicyTypeThe type of the behavior policy.

Definition at line 197 of file async_learning.hpp.

◆ OneStepSarsa

using OneStepSarsa = AsyncLearning<OneStepSarsaWorker<EnvironmentType, NetworkType, UpdaterType, PolicyType>, EnvironmentType, NetworkType, UpdaterType, PolicyType>

Convenient typedef for async one step Sarsa.

Template Parameters
EnvironmentTypeThe type of the reinforcement learning task.
NetworkTypeThe type of the network model.
UpdaterTypeThe type of the optimizer.
PolicyTypeThe type of the behavior policy.

Definition at line 215 of file async_learning.hpp.