Particle deprivation in POMCP at the end of the trial about pomdp-py

[zkytony]

I had a look and saw that all trials have a much higher count for particle reinvigoration at the last time step compared to others

Having high particle reinvigoration could be totally normal. It's a different issue from particle deprivation. If the number keeps growing, the suggests somehow the true observation is less predictable from the current particles. That might be a property of the problem itself.

Since trials are independent (i.e., I am creating a new instance of the problem for every trial and resetting the belief), I wonder if it makes sense to update the belief when the trial ends at all.

Since trials are independent, you only need to make sure the belief is correct at the start of a trial.

[Hororohoruru]

That might be a property of the problem itself

If that were the case, what can I do to avoid this occasional particle deprivation? I can circunvent it by just avoiding the final update, but I am curious about potential solutions

Since trials are independent, you only need to make sure the belief is correct at the start of a trial.

Great, I will do that then, thank you!