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NevarokML: Box Space

The NevarokML plugin provides a Box space implementation, representing a (possibly unbounded) box in R^n. It is commonly used to define the observation space in reinforcement learning environments where the state can have continuous values.

Box Space Overview

The Box space in NevarokML represents a Cartesian product of n closed intervals in R^n. It can have either an identical bound for each dimension or independent bounds for each dimension. Here are the key features and parameters of the Box space:

  • owner: Parameter represents the owner of the space object, usually the object creating the space.
  • size (Shape): The shape of the box space.
  • min (Low): The lower bound of the box, specifying the minimum value for each dimension.
  • max (High): The upper bound of the box, specifying the maximum value for each dimension.

API

Here is the API for the Box space in NevarokML, along with the corresponding default parameter settings:

#include "Spaces/NevarokMLSpace.h"

UFUNCTION(BlueprintPure, Category = "NevarokML|Space")
static UNevarokMLSpace* Box(UObject* owner, FNevarokMLIndex2D size, const TArray<float>& min, const TArray<float>& max)

To create a Box space, call the Box factory function and provide the required parameters. The function will return an instance of the UNevarokMLSpace class, representing the Box space.