Catalano.MachineLearning.Exploration

Class RouletteWheelExploration

java.lang.Object

Catalano.MachineLearning.Exploration.RouletteWheelExploration

All Implemented Interfaces:

IExplorationPolicy

public class RouletteWheelExploration
extends java.lang.Object
implements IExplorationPolicy

The class implements roulette whell exploration policy. Acording to the policy, action a at state s is selected with the next probability: Q( s, a ) p( s, a ) = ------------------ SUM( Q( s, b ) ) b where Q(s, a) is action's a estimation (usefulness) at state s. The exploration policy may be applied only in cases, when action estimates (usefulness) are represented with positive value greater then 0.

Constructor Summary

Constructors

Constructor and Description
RouletteWheelExploration() Initializes a new instance of the RouletteWheelExploration class.

Method Summary

Modifier and Type	Method and Description
int	ChooseAction(double[] actionEstimates) The method chooses an action depending on the provided estimates.

Methods inherited from class java.lang.Object

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

Constructor Detail

RouletteWheelExploration

public RouletteWheelExploration()

Initializes a new instance of the RouletteWheelExploration class.

Method Detail

ChooseAction

public int ChooseAction(double[] actionEstimates)

Description copied from interface: IExplorationPolicy

The method chooses an action depending on the provided estimates. the estimates can be any sort of estimate, which values usefulness of the action (expected summary reward, discounted reward, etc).

Specified by:

ChooseAction in interface IExplorationPolicy

Parameters:

actionEstimates - Action estimates.

Returns:

Returns selected action.