!!!VOID NO LONG PURSUING THIS PROPOSAL !!
Using Randomly Assigned Neurons to Review Proposals
High level Summary:
- A proposal is submitted to the NNS.
- Randomly chosen neurons are assigned to check if the proposal meets minimum community standards.
- Neurons are selected based on voting power weight class.
- A 2/3rds threshold must be met for the proposal to be deemed valid based on established standards. 24 hours are given to vote
- If a 2/3rds majority is not achieved a second round starts where inactive neurons are replaced with trusted neurons that are known to be active.
- If the majority decides the proposal is invalid, the proposal is removed.
- If a majority cannot be achieved the proposal is removed
- If the majority decides the proposal is valid, the proposal is suspended for 3 days and a forum post is created for further deliberation.
- After 3 days of deliberation the proposal is unlocked for voting.
- Those who participated in the proposal review will be given a reward multiplier attached to the neuron that participated for a set amount of time, like a month.
- During the month that the reward multiplier is in effect those neurons have a lower percentage of being chosen again. If they are chosen again they do not receive extra rewards. Rewards are capped.
Key mechanisms:
1. Standards for proposals:
First a clear standard or guide must be defined so all participants are aware of their goals when filtering out proposals.
Those standards can include: 1) clear description of the objective of the proposal and what actions are being requested, 2) clear description of the problem being solved, 3) timeline and link to deliberation of proposal before it was submitted to the NNS, 4) no advertising or solicitation for personal or organization gain, 5)âŠpotentially other criteria TBD.
Diego put together that he considers best practice for motion proposals.
https://wiki.internetcomputer.org/wiki/How-To:_Create_an_NNS_motion_proposal
2. Rewards for participation -
Time based voting reward multiplier:
Rewards are a time based bonus multiplier added to the neurons reward formula. Maybe an extra 1.00 multiplier added to voting rewards for the next month or so.
While a neuron is receiving this reward multiplier it has a much lower probability of being selected again.
Rewards are capped and cannot be accumulated.
Example: if I am selected to participate in a proposal review layer. Once I vote and the proposal either passes or is removed, I begin receiving the reward bonus. The reward bonus is not malleable, if a neuron is split or merged it will remove the reward bonus further incentivizing keeping neurons static. For that month your neuron will have a lower probability of being chosen again (you do not get more rewards if chosen). This incentivizes the user to vote on all other upcoming proposals to take advantage of their time bonus.
Time locked voting rewards ensure individuals are further dissuaded from spamming proposals to game the system. It also ensures there is equal opportunity for everyone in the NNS to gain a chance at collecting proposal review rewards.
3. Supermajority Threshold Trigger: (core mechanism)
Voting power is not used at this stage, neurons should not have more sway then other neurons on what constitutes a valid proposal.
Standards should be baseline for all neurons.
A 2/3rds vote majority threshold. After a 24 hour period if there are neurons that did not vote, those neurons are replaced by âknown activeâ neurons. Another 24 hours is given or until the supermajority threshold is achieved.
âknown activeâ neurons are neurons that have been known to frequently participate in NNS proposal reviews and are given first priority when replacing an inactive neuron.
Indefinite: If the proposal is indefinite (a majority cannot be achieved) it is removed (rework and try again)
Non valid: if the proposal is not valid ( majority vote against it) it is removed (rework and try again)
Valid: if the neuron is valid (majority vote for it) it immediately fires a forum post for discussion and the proposal is locked but viewable in the NNS.
4. Forum Post for Deliberation:
If the proposal is valid, it triggers a forum post where proposals can be deliberated with two way communication between proposal lead and the community.
A 2 to 3 day time period should be set before the proposal unlocks into the NNS
Conclusion:
The aim was to create a simple as possible proposal action potential which is adaptable, can scale as the ICP population increases without causing extra taxation on the system, provides fairness among all holders, and can at its very basic filter proposals for spam/quality assurance.
Key Features
Scaling:
Takes advantage of the current NNS using existing neurons in the network to create a different pattern for reviewing. As the network grows more proposals will be submitted and also more neurons will be staked, meaning more voting groups can be created autonomously. It scales proportionally to size.
Simplicity and modularity
The Proposal review stage can be extended or reduced as we see fit and it can have as many layers as we see fit as well. We can attach and detach features from it as we see fit due to its simple core mechanism.
Future proofing
The proposal was made with People parties in mind, meaning when people parties are eventually developed. This system will meld perfectly with the peopleâs parties concept. People parties would also help further simplify this workflow and remove a lot of the need to provide behavior catching solutions. The neuron bracketing system could be removed entirely or it could be further improved upon. Time locking neurons could also be removed entirely creating further randomization and decentralization.
Split neuron solution/random neuron selection process
Problem:
Random selection of neurons becomes an issue due to the mechanism which allows neurons to split into much smaller neurons with a minimum amount of 1 ICP per neuron. A neuron with 1 million ICP can split itself 1 million times. In theory a group of large neurons could collectively compile a 51% attack and heavily sway randomized proposal reviews or fixed rewards.
Unfortunately we cannot fully resolve this issue until people parties are developed, all we can do is attempt to mitigate system gaming behaviors until people parties become active.
Solution:
Dividing neurons by voting power weight classes
By subdividing neurons into brackets based on voting power weight classes we can determine how much representation each weight class receives and how many seats are allocated to each class. Although this is not the most decentralized way to go about this it ensures equal representation among groups and further incentivizes keeping neurons static.
Example: 5 seats are allocated to neurons with 0 to 100 voting power, 4 seats are allocated to neurons with 100 to 200 voting power, 3 seats to neurons with 300 to 400 voting power, and so on and so on. Since a limited amount of seats are based on the amount of neurons in each group it is more beneficial to keep your neurons as fat as possible. If you split your large neuron there is a higher chance you wonât get selected and if it is selected only a part of your split neuron will be rewarded instead of your full initial fat neuron.
The neuron bracketing system can be removed and replaced when peopleâs parties become active. (no longer necessary)
Let me know what you think or if you need clarification. Thank you.