burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit

Interface DifferentiableVInit

All Superinterfaces:

ValueFunction, ValueFunctionInitialization

All Known Implementing Classes:

DifferentiableVInit.ParamedDiffVInit, LinearDiffRFVInit, LinearStateDiffVF, VanillaDiffVinit

public interface DifferentiableVInit
extends ValueFunctionInitialization

An interface for value function initialization that is differentiable with respect to some parameters. This interface is useful for DifferentiableSparseSampling which may be used to learn the value of leaf nodes in a finite horizon planner.

Author:

James MacGlashan.

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static class	DifferentiableVInit.ParamedDiffVInit A abstract class for DifferentiableVInit that includes a double array of parameters and methods to modify them.

Nested classes/interfaces inherited from interface burlap.behavior.singleagent.ValueFunctionInitialization

ValueFunctionInitialization.ConstantValueFunctionInitialization

Method Summary

Methods

Modifier and Type	Method and Description
double[]	getQGradient(State s, AbstractGroundedAction ga) Returns the Q-value function gradient.
double[]	getVGradient(State s) Returns the value function gradient.

Methods inherited from interface burlap.behavior.singleagent.ValueFunctionInitialization

qValue

Methods inherited from interface burlap.behavior.singleagent.planning.ValueFunction

value

Method Detail

getVGradient

double[] getVGradient(State s)

Returns the value function gradient.

Parameters:

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

Returns:

the value function gradient.

getQGradient

double[] getQGradient(State s,
                    AbstractGroundedAction ga)

Returns the Q-value function gradient.

Parameters:

s - the state on which the Q-value is to be evaluated.

ga - the action on which the Q-value is to be evaluated.

Returns:

the Q-value function gradient