Constant baseline solution ~60 reward

Just guys if you are wondering - for baseline comparison
action = [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.7, 0.1, 0.1, 0.1, 0.886927] * 2
gives you about ~60 reward, more or less depends on starting position etc.

How I found it? I tried to make a symmetric vector of constant parameters and started from [0.1] * 22. Then I pulled each muscle and observed through visualisation the effect of it.
After founding that [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.7, 0.1, 0.1, 0.1, 0.8] stands a little longer than usual (e.g. 10 reward), I manually tuned 0.8 coefficient to make longest standing. I tuned 0.8 coefficient manually via binary search, that’s why it is so weird looking.

I spend like 1 hour for it, it is an easy one solution.

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Different reward on local and remote environments

We have same issues. Our RL model could score 100+ on local, and score like 14 on remote.

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Any discord server?

Do you have a discord server?

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