Uses of Class
neqsim.process.ml.ActionVector

Packages that use ActionVector

Package	Description
neqsim.process.ml	Machine Learning and AI integration for NeqSim.
neqsim.process.ml.examples	Example RL environments demonstrating NeqSim ML integration.

Uses of ActionVector in neqsim.process.ml

Fields in neqsim.process.ml declared as ActionVector

Modifier and Type	Field	Description
private final ActionVector	RLEnvironment.actionSpace

Methods in neqsim.process.ml that return ActionVector

Modifier and Type	Method	Description
ActionVector	ActionVector.define(String name, double lowerBound, double upperBound, String unit)	Define an action dimension with bounds.
ActionVector	RLEnvironment.getActionSpace()	Get the action space specification.
ActionVector	ActionVector.set(String name, double value)	Set an action value, clamping to bounds.
ActionVector	ActionVector.setFromNormalizedArray(double[] normalizedValues)	Set all actions from normalized array.
ActionVector	ActionVector.setNormalized(String name, double normalizedValue)	Set action from normalized value [0, 1].

Methods in neqsim.process.ml with parameters of type ActionVector

Modifier and Type	Method	Description
protected void	RLEnvironment.applyAction(ActionVector action)	Apply action to process equipment.
protected double	RLEnvironment.computeReward(StateVector state, ActionVector action, RLEnvironment.StepInfo info)	Compute reward for current state and action.
RLEnvironment.StepResult	RLEnvironment.step(ActionVector action)	Execute one simulation step with given action.

Uses of ActionVector in neqsim.process.ml.examples

Methods in neqsim.process.ml.examples with parameters of type ActionVector

Modifier and Type	Method	Description
protected void	SeparatorLevelControlEnv.applyAction(ActionVector action)
protected double	SeparatorLevelControlEnv.computeReward(StateVector state, ActionVector action, RLEnvironment.StepInfo info)