Title: Evolutionary Stability of Reputation Management System in Peer to Peer Networks,
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.