SimpleDQN< NetworkType > Class Template Reference

Public Member Functions
	SimpleDQN ()
	Default constructor. More...
	SimpleDQN (const int inputDim, const int h1, const int h2, const int outputDim, const bool isNoisy=false)
	Construct an instance of SimpleDQN class. More...
	SimpleDQN (NetworkType network, const bool isNoisy=false)
void	Backward (const arma::mat state, arma::mat &target, arma::mat &gradient)
	Perform the backward pass of the state in real batch mode. More...
void	Forward (const arma::mat state, arma::mat &target)
	Perform the forward pass of the states in real batch mode. More...
const arma::mat &	Parameters () const
	Return the Parameters. More...
arma::mat &	Parameters ()
	Modify the Parameters. More...
void	Predict (const arma::mat state, arma::mat &actionValue)
	Predict the responses to a given set of predictors. More...
void	ResetNoise ()
	Resets noise of the network, if the network is of type noisy. More...
void	ResetParameters ()
	Resets the parameters of the network. More...

Detailed Description

template<typename NetworkType = FFN<MeanSquaredError<>, GaussianInitialization>>
class mlpack::rl::SimpleDQN< NetworkType >

Template Parameters

NetworkType

The type of network used for simple dqn.

Definition at line 31 of file simple_dqn.hpp.

Constructor & Destructor Documentation

SimpleDQN() [1/3]

SimpleDQN ( )

inline

Default constructor.

Definition at line 37 of file simple_dqn.hpp.

SimpleDQN() [2/3]

SimpleDQN ( const int  inputDim, const int  h1, const int  h2, const int  outputDim, const bool  isNoisy = false  )

inline

Construct an instance of SimpleDQN class.

Parameters

inputDim	Number of inputs.
h1	Number of neurons in hiddenlayer-1.
h2	Number of neurons in hiddenlayer-2.
outputDim	Number of neurons in output layer.
isNoisy	Specifies whether the network needs to be of type noisy.

Definition at line 49 of file simple_dqn.hpp.

SimpleDQN() [3/3]

SimpleDQN ( NetworkType  network, const bool  isNoisy = false  )

inline

Definition at line 75 of file simple_dqn.hpp.

Member Function Documentation

Backward()

void Backward ( const arma::mat  state, arma::mat &  target, arma::mat &  gradient  )

inline

Perform the backward pass of the state in real batch mode.

Parameters

state	The input state.
target	The training target.
gradient	The gradient.

Definition at line 139 of file simple_dqn.hpp.

Forward()

void Forward ( const arma::mat  state, arma::mat &  target  )

inline

Perform the forward pass of the states in real batch mode.

Parameters

state	The input state.
target	The predicted target.

Definition at line 102 of file simple_dqn.hpp.

Parameters() [1/2]

const arma::mat& Parameters ( ) const

inline

Return the Parameters.

Definition at line 128 of file simple_dqn.hpp.

Parameters() [2/2]

arma::mat& Parameters ( )

inline

Modify the Parameters.

Definition at line 130 of file simple_dqn.hpp.

Predict()

void Predict ( const arma::mat  state, arma::mat &  actionValue  )

inline

Predict the responses to a given set of predictors.

The responses will reflect the output of the given output layer as returned by the output layer function.

If you want to pass in a parameter and discard the original parameter object, be sure to use std::move to avoid unnecessary copy.

Parameters

state	Input state.
actionValue	Matrix to put output action values of states input.

Definition at line 91 of file simple_dqn.hpp.

ResetNoise()

void ResetNoise ( )

inline

Resets noise of the network, if the network is of type noisy.

Definition at line 118 of file simple_dqn.hpp.

ResetParameters()

void ResetParameters ( )

inline

Resets the parameters of the network.

Definition at line 110 of file simple_dqn.hpp.

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The documentation for this class was generated from the following file:

• /var/www/mlpack.ratml.org/mlpack.org/_src/mlpack-3.3.2/src/mlpack/methods/reinforcement_learning/q_networks/simple_dqn.hpp