Cost of Control (Metrics discussion)

[AngelaKTE]

Description

• Goal: We measure how many voters have to be added or removed at minimum to achieve a certain funding increase
• Why here?:
  • Optimism knows how many voters and what voters are eligible to vote in Retro Funding
  • in every round, badgeholders can decide whether they participate in a voting or not
  • a malicious actor could convince voters to abstain from voting in order to increase the funding results
  • also, since Optimism is trying to increase the number of voters, malicious voters could convince new voters to take part just to manipulate the result
• How we model it:
  • in every round:
    • we define the desired funding increase (as a constant, e.g. 20%)
    • we randomly assign votes to projects
    • we iterate over all projects to find out which one needs the minimum of voters to be added/removed to reach the target funding increase
    • we add/remove voters accordingly
    • we measure the average minimum per round (across all projects?)
  • many rounds:
    we run many rounds and measure the average minimum number of voters required
  • all voting rules:
    we compare the results over all voting rules
• Chart:
  • average of all rounds, plotting a line chart
  • x-axis: min. decrease/increase of voters (average minimum)
  • y-axis: funding increase
• Scenarios:
  • Model for $10K / $50K / $100K / $500K funding increase
  • we can translate these values to a % based on the scenario design, it's just important to give readers a picture of the absolute value in OP tokens

Open questions:

• Token allocation only integers for voters? @a.kreitenweis to check with Optimism

[linear]

GOV-33 Cost of Control (Metrics discussion)

Description

• Goal: We measure how many voters have to be added or removed at minimum to achieve a certain funding increase
• Why here?:
  • Optimism knows how many voters and what voters are eligible to vote in Retro Funding
  • in every round, badgeholders can decide whether they participate in a voting or not
  • a malicious actor could convince voters to abstain from voting in order to increase the funding results
  • also, since Optimism is trying to increase the number of voters, malicious voters could convince new voters to take part just to manipulate the result
• How we model it:
  • in every round:
    • we randomly assign votes to projects
    • we iterate over all projects to find out which one needs the minimum of votes increase to reach to reach the target funding increase
    • we add voters accordingly
  • many rounds:
    we run many rounds and measure the average minimum number of voters required
  • all voting rules:
    we compare the results over all voting rules
• Chart:
  • average of all round, plotting a line chart
  • x-axis: min. decrease/increase of voters (average minimum)
  • y-axis: funding increase
• Scenarios:
  • Model for $10K / $50K / $100K / $500K funding increase
  • we can translate these values to a % based on the scenario design, it's just important to give readers a picture of the absolute value in OP tokens

Open questions:

• Token allocation only integers for voters? @a.kreitenweis to check with Optimism