NS-Gym Scheduler Module

class ns_gym.schedulers.RandomScheduler(probability=0.5, start=0, end=inf, seed=None)

Bases: Scheduler

Random event scheduler: Events occur randomly with a given probability at each time step.

Parameters:

• probability (float) – The probability of an event occurring at each time step.

• start (int, optional) – The start time for the scheduler. Defaults to 0.

• end (int, optional) – The end time for the scheduler. Defaults to infinity.

• seed (int, optional) – Random generator seed. Defaults to None.

class ns_gym.schedulers.CustomScheduler(event_function, start=0, end=inf)

Bases: Scheduler

Custom event scheduler: Allows for custom event logic based on a user-defined function.

class ns_gym.schedulers.ContinuousScheduler(start=0, end=inf)

Bases: Scheduler

Continuous Event Scheduler : At every time step return true

class ns_gym.schedulers.DiscreteScheduler(event_list, start=0, end=inf)

Bases: Scheduler

A discrete event scheduler returns a bool indicating where the system should transition at this time step

Parameters:

event_list (set) – List of time steps to make a transition

class ns_gym.schedulers.PeriodicScheduler(period, start=0, end=inf)

Bases: Scheduler

Periodic event scheduler: At periodic steps return true.

Parameters:

period (int) – Period of event transition times.

class ns_gym.schedulers.MemorylessScheduler(p, start=0, end=inf, seed=None)

Bases: Scheduler

Memoryless Scheduler: Events happen at intervals according to a Geometric distribution

This scheduler models the number of trials that must be run before a success. The scheduler samples from a geometric distribution then records the new time an event will occur. After a transition we resample from the geometric distribution.

Parameters:

• p (float) – The probability of success of an individual trial.

• seed (int, optional) – Random generator seed. Defaults to None.