RlEnv

All Implemented Interfaces:
```
public final class RlEnv

                    
```
Reinforcement Learning Environment for Queueing Networks Provides an interface for RL agents to interact with queueing network models

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description

Field Summary

Fields
Modifier and Type	Field	Description
`private final Network`	`model`
`private final Integer`	`actionSize`
`private final IntArray`	`idxOfQueueInNodes`
`private final IntArray`	`idxOfSourceInNodes`
`private final Integer`	`stateSize`
`private final Double`	`gamma`

Constructor Summary

Constructors
Constructor	Description
`RlEnv(Network model, IntArray idxOfQueueInNodes, IntArray idxOfSourceInNodes, Integer stateSize, Double gamma)`

Enum Constant Summary

Enum Constants
Enum Constant	Description

Method Summary

Modifier and Type	Method	Description
`final Network`	`getModel()`
`final Integer`	`getActionSize()`
`final IntArray`	`getIdxOfQueueInNodes()`
`final IntArray`	`getIdxOfSourceInNodes()`
`final Integer`	`getStateSize()`
`final Double`	`getGamma()`
`final Boolean`	`isInStateSpace(Array<?> nodes)`	Check if the current node states are within the defined state space
`final Boolean`	`isInActionSpace(Array<?> nodes)`	Check if the current node states are within the action space
`final Pair<Double, Integer>`	`sample()`	Sample the next event from the queueing network Returns the time until next event and the node where departure occursNOTE: This is a placeholder implementation.
`final Unit`	`update(IntArray newState)`	Update the model state after an action/eventNOTE: This is a placeholder implementation.
`final Unit`	`reset()`	Reset the environment to initial state

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - RlEnv
```
RlEnv(Network model, IntArray idxOfQueueInNodes, IntArray idxOfSourceInNodes, Integer stateSize, Double gamma)
```
- Method Detail
  - getModel
```
 final Network getModel()
```
  - getActionSize
```
 final Integer getActionSize()
```
  - getIdxOfQueueInNodes
```
 final IntArray getIdxOfQueueInNodes()
```
  - getIdxOfSourceInNodes
```
 final IntArray getIdxOfSourceInNodes()
```
  - getStateSize
```
 final Integer getStateSize()
```
  - getGamma
```
 final Double getGamma()
```
  - isInStateSpace
```
 final Boolean isInStateSpace(Array<?> nodes)
```
    Check if the current node states are within the defined state space
  - isInActionSpace
```
 final Boolean isInActionSpace(Array<?> nodes)
```
    Check if the current node states are within the action space
  - sample
```
 final Pair<Double, Integer> sample()
```
    Sample the next event from the queueing network Returns the time until next event and the node where departure occurs
    NOTE: This is a placeholder implementation. In the actual implementation, this would use SolverSSA.
  - update
```
 final Unit update(IntArray newState)
```
    Update the model state after an action/event
    NOTE: This is a placeholder implementation.
  - reset
```
 final Unit reset()
```
    Reset the environment to initial state