Introducing Learning & Saturation Effects into Neuron Voting Power Attribution

[ankeliu]

An improved Voting Power Attribution system for neuron weights inspired by learning curves could significantly support new members gain voting power more quickly (right now, veteran members have significant benefit over new members, which is the problem we need to solve). BlockScience proposed a learning/saturation aware neuron embedded on a 3rd layer.

The total vote power should accrue slowly initially, accelerate (e.g. increase the marginal power per newly participated round) until it hits a inflection point, on which it deaccelerates until it hits a asymptotic level, which can either be a slowly-growing slope or a constant.