Scotbot: convergent_linear reward curves are supported
Each scot has now two new parameters:
post_reward_curve
- can bedefault
,convergent_linear
post_reward_curve_parameter
- can be None or a float number
Default setting is post_reward_curve=default
and post_reward_curve_parameter=None
, which means that the post reward is calculated by
weight_rshares = rshares ^ config[token]["author_curve_exponent"]
When post_reward_curve
is set to convergent_linear
, the post reward is calculated by:
s = config[token]["post_reward_curve_parameter"]
weight_rshares = ( rshares * rshares ) / ( rshares + s )
and config[token]["author_curve_exponent"] is not used for calculation.
Comparison
Lets assume there is a pool of 2 TOKEN and there are three posts with 500, 1500 and 10000 rshares
default settings
author curve exponent | rshares | weight_rshares | payout |
---|---|---|---|
1.0 | 500 | 500 | 0.08 |
1.0 | 1500 | 1500 | 0.25 |
1.0 | 10000 | 10000 | 1.67 |
1.05 | 500 | 682 | 0.07 |
1.05 | 1500 | 2162 | 0.23 |
1.05 | 10000 | 15848 | 1.7 |
1.1 | 500 | 930 | 0.06 |
1.1 | 1500 | 3116 | 0.21 |
1.1 | 10000 | 25118 | 1.72 |
1.3 | 500 | 3225 | 0.04 |
1.3 | 1500 | 13456 | 0.15 |
1.3 | 10000 | 158489 | 1.81 |
1.5 | 500 | 11180 | 0.02 |
1.5 | 1500 | 58094 | 0.11 |
1.5 | 10000 | 1000000 | 1.87 |
convergent_linear
post reward curve parameter | rshares | weight_rshares | payout |
---|---|---|---|
10 | 500 | 490 | 0.08 |
10 | 1500 | 1490 | 0.25 |
10 | 10000 | 9990 | 1.67 |
100 | 500 | 416 | 0.07 |
100 | 1500 | 1406 | 0.24 |
100 | 10000 | 9900 | 1.69 |
1000 | 500 | 166 | 0.03 |
1000 | 1500 | 900 | 0.18 |
1000 | 10000 | 9090 | 1.79 |
10000 | 500 | 23 | 0.01 |
10000 | 1500 | 195 | 0.07 |
10000 | 10000 | 5000 | 1.92 |
Conclusion
When using the convergent_linear cuve, the parameter can be used to decide from which reward to should convert to a linear curve. For post_reward_curve_parameter=10
, the payout is the same as for exponent = 1.
For post_reward_curve_parameter = 1000, the rshares for the post with 500 rshares are weighted with 0.33, the post with 1500 rshares is weighted with 0.6 and the post with 10000 rshares is weighted with 0.909.
Thus, convergent_linear
with a parameter of 1000 can be used to reduce the payout of post with less than 1000 rshares.
Let me know when you want to change the configuration for your SCOT.
Just wondering, do you know if Palnet has a limit of one post per day?
I posted two post last night both with the palnet tag and my second post my @actifit post did not post to palnet???🤔
Edit the post and change the tag to lowercase. It's registered as Palnet instead of palnet on the chain for some reason and it causes the bug.
Thank you, so nice to have Steem-engine and palnet!!
Exciting times to come!!!👍🤗
Sorry to bother you again, maybe you can help. I posted my @actifit post for July 1st and edited the post on steemit adding photo's and I rechecked to make sure palnet was lower case.
Nothing posts to PAL, this is two post in a row. I have reached out to PAL tonight on discord, I'm just scratching my head, trying to figure out how to fix this ....
Thanks again @silvertop... Mike
Hmmm, I know they're working on fixing it to automatically read it either way, I guess it's possible that changing it isn't picking up. I know people have added the tag to posts that didn't have it before. Maybe just make sure in the future they're lowercase, but it should be fixed soon either way.
Thanks @clayboyn, Tomorrow when I post my @actifit I will edit and add the photo's on steempeak instead of steemit to see if this helps.
Because @actifit post from my IOS I can't just initially post to PAL....
Have a good one!! :)
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Would be cool to have n x S^log(n) curves as well.
I will look into them. Do you have a name for them?
Posted using Partiko Android
Isn't this a design flaw that a name is required instead of just using the formula?
And still no witness vote by @aggroed for you, Holger...
So, if i read that math right, we are getting a sublinear curve.
Small votes are going down exponentially while large votes will go up due to smaller votes counting for even less in the math, yes?
Yes
Did you change the curation formula too? https://github.com/steemit/steem/blob/master/libraries/chain/util/reward.cpp#L103
This is also where all the other formulas used in the past are.
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