How Does the Blurt Blockchain Convergent Linear Rewards Curve Work?
The Blurt blockchain inherited the convergent linear rewards curve from it's STEEM predecessor. The convergent linear curve was introduced to STEEM following HF21, in August of 2019.
The convergent linear rewards curve n^2 / (n + 1) starts off as a super linear and then gradually converges on linear as the name suggests.
The convergent linear curve was proposed as a middle grounds between super linear and linear, providing some of the benefits of both of the curves simultaneously.
Linear vs Super Linear [quadratic] vs Convergent Linear
Let's look at the benefits of each of these three models, and you can decide for yourself which one you like best.
(Image Credit: @vandeberg)
Considered the most "fair" because each unit of rshares is worth the same amount of rewards regardless if you have a large stake or a small stake. If i vote with 100 BLURT and you vote with 200 BLURT you will always receive exactly double the rewards that I will.
This is considered good for lower and middle stake holders as the rewards are representative to the weight of your vote and is not weighted towards the larger stake. The main disadvantages is that it encourages self-votes, and there's no added incentive for large accounts to curate.
The Linear rewards curve was introduces to STEEM following HF19 on June 20, 2017 to replace the "unfair" super linear curve that was in place from the beginning. Eventually it would be replaced by the convergent linear curve down the road following HF21, in August of 2019.
Quadratic/Super Linear [Red Curve]
The original rewards curve! Launched with STEEM as n^3 but was subsequently changed to n^2 before the first payout on July 4th, 2016. The n^2 curve has the draw back of becoming more and more unfair as rshares on a post increase.
This has the effect of encouraging whales to only vote on popular posts. The larger the vote, the more the rewards are weighted in their favor. A benefit is that it encourages consolidating stake in order to maximize rewards. It also encourages curation from large account, which is a benefit unless those votes are only going to popular posts.
Convergent Linear [Green Curve]
Considered the best of both worlds, as it encourages curation from larger accounts, but at the same time as the post earns larger and larger rewards the curve gradually converges towards linear where equal earning per rshare is more possible.
This also encourages voting on quality content not necessarily the most popular content. Provides some incentive for larger accounts to curate and at the same time flattens the curve somewhat making rewards per rshare more fair.
A Brief History of the Rewards Curve
- Genesis - Super Linear Rewards Curve - n^2
- HF 19 - Linear Rewards Curve - f(x) = x
- HF 21 - Convergent Linear Rewards Curve - n^2 / (n + 1)
I hope this information was presented in a clear and concise way. I'm not much of a math person so I tried to steer clear of referencing formulas. There are others that are experts in the department for sure, I'll leave that up to them.
I think it's helpful to know where we came from, and how we got here in order to decide the best direction for the future of the Blurt rewards curve.
As always open for comments and suggestion in the comment section below.
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