It is used to update the models from experiences stored in the experience replay object. It uses longer experience sequences to enhance reinforcement learning.
Creates a new PrioritizedExperienceReplay object.
PrioritizedExperienceReplay.new(batchSize: number, numberOfRunsToUpdate: number, maxBufferSize: number, nStep: number)
batchSize: The number of experience to sample from for training.
numberOfRunsToUpdate: The number of run() function needed to be called to run a single event of experience replay.
maxBufferSize: The maximum number of experiences that can be kept inside the object.
nStep: The maximum length of experience sequences to be sampled.
Change the parameters of an experience replay object.
PrioritizedExperienceReplay:setParametersbatchSize: number, numberOfRunsToUpdate: number, maxBufferSize: number, nStep: number)
batchSize: The number of experience to sample from for training.
numberOfRunsToUpdate: The number of run() function needed to be called to run a single event of experience replay.
maxBufferSize: The maximum number of experiences that can be kept inside the object.
nStep: The maximum length of experience sequences to be sampled.