burlap.behavior.policy

Class BoltzmannQPolicy

java.lang.Object

burlap.behavior.policy.Policy

burlap.behavior.policy.BoltzmannQPolicy

All Implemented Interfaces:

SolverDerivedPolicy

public class BoltzmannQPolicy
extends Policy
implements SolverDerivedPolicy

This class implements a Boltzmann policy where the the Q-values represent the components of the Boltzmann distribution. This policy requires a QComputable valueFunction to be passed to it.

Author:

James MacGlashan

Nested Class Summary

Nested classes/interfaces inherited from class burlap.behavior.policy.Policy

Policy.ActionProb, Policy.GroundedAnnotatedAction, Policy.PolicyUndefinedException

Field Summary

Fields

Modifier and Type	Field and Description
protected QFunction	qplanner

Fields inherited from class burlap.behavior.policy.Policy

annotateOptionDecomposition, evaluateDecomposesOptions

Constructor Summary

Constructors

Constructor and Description
BoltzmannQPolicy(double temperature) Initializes with a temperature value.
BoltzmannQPolicy(QFunction planner, double temperature) Initializes with a temperature value and the QComputable valueFunction to use.

Method Summary

Methods

Modifier and Type	Method and Description
AbstractGroundedAction	getAction(State s) This method will return an action sampled by the policy for the given state.
java.util.List<Policy.ActionProb>	getActionDistributionForState(State s) This method will return action probability distribution defined by the policy.
boolean	isDefinedFor(State s) Specifies whether this policy is defined for the input state.
boolean	isStochastic() Indicates whether the policy is stochastic or deterministic.
void	setSolver(MDPSolverInterface solver) Sets the valueFunction whose results affect this policy.

Methods inherited from class burlap.behavior.policy.Policy

evaluateBehavior, evaluateBehavior, evaluateBehavior, evaluateBehavior, evaluateBehavior, evaluateMethodsShouldAnnotateOptionDecomposition, evaluateMethodsShouldDecomposeOption, followAndRecordPolicy, followAndRecordPolicy, getDeterministicPolicy, getProbOfAction, getProbOfActionGivenDistribution, getProbOfActionGivenDistribution, sampleFromActionDistribution

Methods inherited from class java.lang.Object

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

Field Detail

qplanner

protected QFunction qplanner

Constructor Detail

BoltzmannQPolicy

public BoltzmannQPolicy(double temperature)

Initializes with a temperature value. The temperature value controls how greedy the Boltzmann distribution is. The temperature should be positive with values near zero causing the distribution to be more greedy. A high temperature causes the distribution to be more uniform.

Parameters:

temperature - the positive temperature value to use

BoltzmannQPolicy

public BoltzmannQPolicy(QFunction planner,
                double temperature)

Initializes with a temperature value and the QComputable valueFunction to use. The temperature value controls how greedy the Boltzmann distribution is. The temperature should be positive with values near zero causing the distribution to be more greedy. A high temperature causes the distribution to be more uniform.

Parameters:

planner - the q-computable valueFunction to use.

temperature - the positive temperature value to use

Method Detail

getAction

public AbstractGroundedAction getAction(State s)

Description copied from class: Policy

This method will return an action sampled by the policy for the given state. If the defined policy is stochastic, then multiple calls to this method for the same state may return different actions. The sampling should be with respect to defined action distribution that is returned by getActionDistributionForState

Specified by:

getAction in class Policy

Parameters:

s - the state for which an action should be returned

Returns:

a sample action from the action distribution; null if the policy is undefined for s

getActionDistributionForState

public java.util.List<Policy.ActionProb> getActionDistributionForState(State s)

Description copied from class: Policy

This method will return action probability distribution defined by the policy. The action distribution is represented by a list of ActionProb objects, each which specifies a grounded action and a probability of that grounded action being taken. The returned list does not have to include actions with probability 0.

Specified by:

getActionDistributionForState in class Policy

Parameters:

s - the state for which an action distribution should be returned

Returns:

a list of possible actions taken by the policy and their probability.

isStochastic

public boolean isStochastic()

Description copied from class: Policy

Indicates whether the policy is stochastic or deterministic.

Specified by:

isStochastic in class Policy

Returns:

true when the policy is stochastic; false when it is deterministic.

setSolver

public void setSolver(MDPSolverInterface solver)

Description copied from interface: SolverDerivedPolicy

Sets the valueFunction whose results affect this policy.

Specified by:

setSolver in interface SolverDerivedPolicy

Parameters:

solver - the solver from which this policy is derived

isDefinedFor

public boolean isDefinedFor(State s)

Description copied from class: Policy

Specifies whether this policy is defined for the input state.

Specified by:

isDefinedFor in class Policy

Parameters:

s - the input state to test for whether this policy is defined

Returns:

true if this policy is defined for State s, false otherwise.