Consensus: Reputers

Reputers are rewarded based on their accuracy relative to consensus (formed by all reputers providing data for a topic) and stake, with added functionality to prevent centralization of rewards caused by reputers with larger stakes.

Problem: Runaway Centralization

  1. Stake-Weighted Average:
  • Reputers are actors who report how accurate certain predictions or inferences are against the ground truth.
  • Normally, we might average the accuracy (or "losses") they report but give more weight to reputers with bigger stakes (more reputation).
  • This means reputers with more stake have more influence on the consensus (agreed-upon truth).
  1. Runaway Effect:
  • The problem is that reputers with higher stakes will be closer to consensus, which they have more influence on, and get more rewards, which further increases their stakes.
  • This creates a cycle where the rich get richer, leading to centralization. A few reputers end up controlling most of the influence and rewards, which is unfair and unhealthy for the system.

Solution: Adjusted Stake

  1. Adjusted Stake:
  • To prevent runaway centralization, we adjust how much weight each reputer's stake has when setting the consensus.
  • Instead of using the full stake for weighting, we use an adjusted version that doesn’t let any one reputer dominate.
  1. How It Works:
  • The formula for adjusted stake ensures that if a reputer's stake goes above a certain level, it doesn’t keep increasing their weight in the consensus calculation.
  • It levels the playing field, so reputers with smaller stakes still have some influence.

S^im=min(NraimSimmaimSim,1)\hat{S}_{im} = \min \left( \frac{N_r a_{im} S_{im}}{\sum_m a_{im} S_{im}}, 1 \right)

Where:

  • NrN_{r}​ is the number of reputers.
  • aima_{im} is a listening coefficient, which is a measure of how much the network considers each reputer's input, and is optimized to maximize consensus among the reputers.
  • SimS_{im}​ is the original stake.