TrainingConfig Class Reference

Public Member Functions

 TrainingConfig ()
 
 TrainingConfig (size_t numWorkers, size_t updateInterval, size_t targetNetworkSyncInterval, size_t stepLimit, size_t explorationSteps, double stepSize, double discount, double gradientLimit, bool doubleQLearning)
 
double Discount () const
 Get the discount rate for future reward. More...

 
double & Discount ()
 Modify the discount rate for future reward. More...

 
bool DoubleQLearning () const
 Get the indicator of double q-learning. More...

 
bool & DoubleQLearning ()
 Modify the indicator of double q-learning. More...

 
size_t ExplorationSteps () const
 Get the exploration steps. More...

 
size_t & ExplorationSteps ()
 Modify the exploration steps. More...

 
double GradientLimit () const
 Get the limit of update gradient. More...

 
double & GradientLimit ()
 Modify the limit of update gradient. More...

 
size_t NumWorkers () const
 Get the amount of workers. More...

 
size_t & NumWorkers ()
 Modify the amount of workers. More...

 
size_t StepLimit () const
 Get the maximum steps of each episode. More...

 
size_t & StepLimit ()
 Modify the maximum steps of each episode. More...

 
double StepSize () const
 Get the step size of the optimizer. More...

 
double & StepSize ()
 Modify the step size of the optimizer. More...

 
size_t TargetNetworkSyncInterval () const
 Get the interval for syncing target network. More...

 
size_t & TargetNetworkSyncInterval ()
 Modify the interval for syncing target network. More...

 
size_t UpdateInterval () const
 Get the update interval. More...

 
size_t & UpdateInterval ()
 Modify the update interval. More...

 

Detailed Description

Definition at line 19 of file training_config.hpp.

Constructor & Destructor Documentation

◆ TrainingConfig() [1/2]

TrainingConfig ( )
inline

Definition at line 22 of file training_config.hpp.

◆ TrainingConfig() [2/2]

TrainingConfig ( size_t  numWorkers,
size_t  updateInterval,
size_t  targetNetworkSyncInterval,
size_t  stepLimit,
size_t  explorationSteps,
double  stepSize,
double  discount,
double  gradientLimit,
bool  doubleQLearning 
)
inline

Definition at line 31 of file training_config.hpp.

Member Function Documentation

◆ Discount() [1/2]

◆ Discount() [2/2]

double& Discount ( )
inline

Modify the discount rate for future reward.

Definition at line 89 of file training_config.hpp.

◆ DoubleQLearning() [1/2]

bool DoubleQLearning ( ) const
inline

Get the indicator of double q-learning.

Definition at line 97 of file training_config.hpp.

◆ DoubleQLearning() [2/2]

bool& DoubleQLearning ( )
inline

Modify the indicator of double q-learning.

Definition at line 99 of file training_config.hpp.

◆ ExplorationSteps() [1/2]

size_t ExplorationSteps ( ) const
inline

Get the exploration steps.

Definition at line 77 of file training_config.hpp.

◆ ExplorationSteps() [2/2]

size_t& ExplorationSteps ( )
inline

Modify the exploration steps.

Definition at line 79 of file training_config.hpp.

◆ GradientLimit() [1/2]

◆ GradientLimit() [2/2]

double& GradientLimit ( )
inline

Modify the limit of update gradient.

Definition at line 94 of file training_config.hpp.

◆ NumWorkers() [1/2]

size_t NumWorkers ( ) const
inline

Get the amount of workers.

Definition at line 53 of file training_config.hpp.

◆ NumWorkers() [2/2]

size_t& NumWorkers ( )
inline

Modify the amount of workers.

Definition at line 55 of file training_config.hpp.

◆ StepLimit() [1/2]

◆ StepLimit() [2/2]

size_t& StepLimit ( )
inline

Modify the maximum steps of each episode.

Setting it to 0 means no limit.

Definition at line 74 of file training_config.hpp.

◆ StepSize() [1/2]

◆ StepSize() [2/2]

double& StepSize ( )
inline

Modify the step size of the optimizer.

Definition at line 84 of file training_config.hpp.

◆ TargetNetworkSyncInterval() [1/2]

◆ TargetNetworkSyncInterval() [2/2]

size_t& TargetNetworkSyncInterval ( )
inline

Modify the interval for syncing target network.

Definition at line 66 of file training_config.hpp.

◆ UpdateInterval() [1/2]

◆ UpdateInterval() [2/2]

size_t& UpdateInterval ( )
inline

Modify the update interval.

Definition at line 60 of file training_config.hpp.


The documentation for this class was generated from the following file:
  • /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.2.1/src/mlpack/methods/reinforcement_learning/training_config.hpp