Evolutionary Stability of Reputation Management System in Peer to Peer Networks

TL;DR

This paper uses evolutionary game theory to analyze the stability of reputation management in peer-to-peer networks, finding that reputation strategies are unstable without incentives but can be stabilized with initial payments.

Contribution

It introduces a novel evolutionary game model for reputation systems and identifies conditions under which reputation strategies become evolutionarily stable.

Findings

Reputation strategies are unstable without incentives.

Initial payments can stabilize reputation strategies.

A threshold fraction of users calculating reputation ensures stability.

Abstract

Each participant in peer-to-peer network prefers to free-ride on the contribution of other participants. Reputation based resource sharing is a way to control the free riding. Instead of classical game theory we use evolutionary game theory to analyse the reputation based resource sharing in peer to peer system. Classical game-theoretical approach requires global information of the population. However, the evolutionary games only assumes light cognitive capabilities of users, that is, each user imitates the behavior of other user with better payoff. We find that without any extra benefit reputation strategy is not stable in the system. We also find the fraction of users who calculate the reputation for controlling the free riding in equilibrium. In this work first we made a game theoretical model for the reputation system and then we calculate the threshold of the fraction of users with which the reputation strategy is sustainable in the system. We found that in simplistic conditions reputation calculation is not evolutionarily stable strategy but if we impose some initial payment to all users and then distribute that payment among the users who are calculating reputation then reputation is evolutionary stable strategy.