questions about training NBA dataset about imma HOT 4 OPEN

Indeed, it can take a while to obtain results on the NBA dataset. If you would like to expedite it, consider

• increasing the initial learning rate (and increasing the rate of decay).
• increase the interval for logging and evaluation

The results in the paper are obtained by averaging the number over multiple runs with different random seeds.

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Thanks for quick reply!
I have one more question in main.py evaluate function. You write in line 41 that:
constant = 0.3048 if args.env == 'bball' else 1.
I'm wondering why the NBA datasets have to multiply this constant after scaling. Could you please quote some reference or tell me the logic?

Thanks a lot!

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That is to convert the unit from Foot to Meter.

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Indeed, it can take a while to obtain results on the NBA dataset. If you would like to expedite it, consider

• increasing the initial learning rate (and increasing the rate of decay).
• increase the interval for logging and evaluation

The results in the paper are obtained by averaging the number over multiple runs with different random seeds.

could you please share the ade/fde result when training NBA datasets using all default config in your repo? I get a surprisingly low result.

Also, I would like to ask that what's the FPS of the other two datasets( Phase, Social Navigation Environment) you used in the experiement.
Thanks a lot!

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