C# 클래스 Accord.MachineLearning.RouletteWheelExploration

Roulette wheel exploration policy.

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.

상속: IExplorationPolicy

파일 보기 프로젝트 열기: accord-net/framework

공개 메소드들

메소드	설명
ChooseAction ( double actionEstimates ) : int	Choose an action. 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).
RouletteWheelExploration ( ) : System	Initializes a new instance of the RouletteWheelExploration class.

메소드 상세

ChooseAction() 공개 메소드

Choose an action.

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).

public ChooseAction ( double actionEstimates ) : int
actionEstimates	double	Action estimates.
리턴	int

RouletteWheelExploration() 공개 메소드

Initializes a new instance of the RouletteWheelExploration class.

public RouletteWheelExploration ( ) : System
리턴	System