how do I determine the minimum size of replay buffer

I’m training a dqn in unity and it controls a game object using [yaw, lateral vector, and forward vector] as my action space. I’ve read that people obtain a minimum number of experiences for their replay buffer before starting training (on some posts, read that this min is as high as 10000). I see that my model is basically giving me the same action for every inference since it is completely untrained right now. It seems to me that collecting a large amount of such data before I start training will be mostly redundant as it isn’t really trying a variety of actions. If my batch size is 64, is there anything I should be wary of if I want to start training with a replay buffer of (let’s say 256) experiences? I hypothesize that this will help me add variety in my training data earlier on.

I’m a noob so I am very open to being referred to papers that may relate to this, thx in advance.

submitted by /u/ProtectionFrosty5393
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