Reinforcement Learning Toolbox - Experience Buffer Samples
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Hans-Joachim Steinort
am 17 Sep. 2019
Kommentiert: Hans-Joachim Steinort
am 20 Sep. 2019
The simulation I'm running has a fixed-step solver with a fixed-step-size of 5e-4. The sample time of my DQN-Agent (and the corresponding S-function for the reward-signal) is 0.25.
How is it possible that after a simulation time of 20 seconds I have a BufferLength of ~1600 samples? I hope you can enlighten me...
Bonus question:
Is it possible to look into the ExperienceBuffer? As impressed as I am by the RL-Toolbox, I would really prefer it not to be such a blackbox in most cases.
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Raunak Gupta
am 20 Sep. 2019
Hi,
Since it is mentioned that DQN Agent is used, I am assuming that rlDQNAgentOptions is used for setting up the agent properties. The ExperienceBufferLength can be specified for storing that many experiences from training the agent. Also, there is a parameter SaveExperienceBufferWithAgent which can be set to true for saving the Experience buffer while training. The experience upto the limit of ExperienceBufferLength will be stores in a rlDQNAgent Object.
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