Unraveling the Evolution of Defectors in Online Business Games

TL;DR

This paper investigates the evolution of defectors in anonymous online business environments using a genetic algorithm-based SIPD model, finding that compensation reduces defectors but doesn't fully promote cooperation.

Contribution

It introduces a genetic algorithm simulation of the SIPD to analyze defector evolution and the impact of compensation mechanisms in online markets.

Findings

Compensation reduces the population of defectors.

Complete cooperation and trust are not achieved solely through compensation.

Genetic algorithms effectively model evolutionary dynamics in online social dilemmas.

Abstract

Anonymous online business environments have a social dilemma situation in it. A dilemma on whether to cooperate or Defect. Defection by a buyer to seller and/or seller to buyer might give each a better profit at the cost of the loss of other. However, if these parties were to interact in future too, a bad past reference might prevent cooperative actions, thus depriving each other from a better gain. The anonymity of the players and an absence of central governing body still make this environment tempting for the defectors. What might be the evolutionary behavior of defectors in such environment? How could their increasing population be controlled? It is these two questions basically that we attempt to address in this research work. A genetic algorithm based spatial iterated prisoners dilemma (SIPD) environment has been used to simulate the experiments. A case where compensation for the looser is provided by the system is modeled and analyzed through experiments. Our results show that compensation can be useful in decreasing defective population in the society, however, this might not be enough for the evolution of a cooperative and reliable society of trustworthy players.