burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit

Class LinearStateDiffVF

java.lang.Object

burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearStateDiffVF

All Implemented Interfaces:

ParametricFunction, DifferentiableVInit, DifferentiableValueFunction, ValueFunction

public class LinearStateDiffVF
extends java.lang.Object
implements DifferentiableVInit

A class for defining a (differentiable) linear function over state features for value function initialization. This class is useful for learning the value function initialization for leaf nodes of a finite horizon valueFunction with MLIRL.

Author:

James MacGlashan.

Nested Class Summary

Nested classes/interfaces inherited from interface burlap.behavior.functionapproximation.ParametricFunction

ParametricFunction.ParametricStateActionFunction, ParametricFunction.ParametricStateFunction

Field Summary

Fields

Modifier and Type	Field and Description
protected int	dim
protected DenseStateFeatures	fvgen The state feature vector generator over which the linear function operates
protected double[]	parameters

Constructor Summary

Constructors

Constructor and Description
LinearStateDiffVF(DenseStateFeatures fvgen, int dim) Initializes with the state feature vector generator over which the linear function is defined and the dimensionality of it.

Method Summary

Modifier and Type	Method and Description
ParametricFunction	copy() Returns a copy of this ParametricFunction.
double	getParameter(int i) Returns the value of the ith parameter value
int	numParameters() Returns the number of parameters defining this function.
void	resetParameters() Resets the parameters of this function to default values.
void	setParameter(int i, double p) Sets the value of the ith parameter to given value
double	value(State s) Returns the value function evaluation of the given state.
FunctionGradient	valueGradient(State s) Returns the gradient of this value function

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

fvgen

protected DenseStateFeatures fvgen

The state feature vector generator over which the linear function operates

dim

protected int dim

parameters

protected double[] parameters

Constructor Detail

LinearStateDiffVF

public LinearStateDiffVF(DenseStateFeatures fvgen,
                         int dim)

Initializes with the state feature vector generator over which the linear function is defined and the dimensionality of it.

Parameters:

fvgen - the state feature vector generator over which the linear function is defined.

dim - the dimensionality of the feature vector/parameters

Method Detail

numParameters

public int numParameters()

Description copied from interface: ParametricFunction

Returns the number of parameters defining this function. Note that some implementations my have a dynamic number of parameters that grows or shrinks over time. Consult the documentation for the specific implementation for more information.

Specified by:

numParameters in interface ParametricFunction

Returns:

the number of parameters defining this function.

getParameter

public double getParameter(int i)

Description copied from interface: ParametricFunction

Returns the value of the ith parameter value

Specified by:

getParameter in interface ParametricFunction

Parameters:

i - the parameter index

Returns:

the double value of the ith parameter

setParameter

public void setParameter(int i,
                         double p)

Description copied from interface: ParametricFunction

Sets the value of the ith parameter to given value

Specified by:

setParameter in interface ParametricFunction

Parameters:

i - the index of the parameter to set

p - the parameter value to which it should be set

resetParameters

public void resetParameters()

Description copied from interface: ParametricFunction

Resets the parameters of this function to default values.

Specified by:

resetParameters in interface ParametricFunction

copy

public ParametricFunction copy()

Description copied from interface: ParametricFunction

Returns a copy of this ParametricFunction.

Specified by:

copy in interface ParametricFunction

Returns:

a copy of this ParametricFunction.

valueGradient

public FunctionGradient valueGradient(State s)

Description copied from interface: DifferentiableValueFunction

Returns the gradient of this value function

Specified by:

valueGradient in interface DifferentiableValueFunction

Parameters:

s - the state on which the function is to be evaluated

Returns:

the gradient of this value function

value

public double value(State s)

Description copied from interface: ValueFunction

Returns the value function evaluation of the given state. If the value is not stored, then the default value specified by the ValueFunctionInitialization object of this class is returned.

Specified by:

value in interface ValueFunction

Parameters:

s - the state to evaluate.

Returns:

the value function evaluation of the given state.