Class GaussianNoiseExploration<T>

Namespace

AiDotNet.ReinforcementLearning.Policies.Exploration

Assembly

AiDotNet.dll

Gaussian noise exploration for continuous action spaces.

public class GaussianNoiseExploration<T> : ExplorationStrategyBase<T>, IExplorationStrategy<T>

Type Parameters

T

The numeric type used for calculations.

Inheritance

object

ExplorationStrategyBase<T>

GaussianNoiseExploration<T>

Implements

IExplorationStrategy<T>

Inherited Members

ExplorationStrategyBase<T>.NumOps

ExplorationStrategyBase<T>.BoxMullerSample(Random)

ExplorationStrategyBase<T>.ClampAction(Vector<T>, double, double)

ExplorationStrategyBase<T>.ValidateActionSize(int, int, string)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

GaussianNoiseExploration(double, double, double)

public GaussianNoiseExploration(double initialStdDev = 0.1, double noiseDecay = 0.995, double minNoise = 0.01)

Parameters

initialStdDev double

noiseDecay double

minNoise double

Properties

CurrentNoiseStdDev

public double CurrentNoiseStdDev { get; }

Property Value

double

Methods

GetExplorationAction(Vector<T>, Vector<T>, int, Random)

Modifies or replaces the policy's action for exploration.

public override Vector<T> GetExplorationAction(Vector<T> state, Vector<T> policyAction, int actionSpaceSize, Random random)

Parameters

state Vector<T>

The current state.

policyAction Vector<T>

The action suggested by the policy.

actionSpaceSize int

The number of possible actions.

random Random

Random number generator for stochastic exploration.

Returns

Vector<T>

The action to take after applying exploration.

Reset()

Resets internal state (e.g., for new episodes or training sessions).

public override void Reset()

Update()

Updates internal parameters (e.g., epsilon decay, noise reduction). Called after each training step.

public override void Update()