Fingerprint analysis of the noisy prisoner's dilemma

Abstract— Fingerprinting is a technique that permits automatic classification of strategies for playing a game. In this study the evolution of strategies for playing the iterated prisoner’s dilemma at three different noise levels is analyzed using fingerprinting and other techniques including a novel quantity, evolutionary velocity, derived from fingerprinting. The results are at odds with initial expectations and permit the detection of a critical difference in the evolution of agents with and without noise. Noise during fitness evaluation places a larger fraction of an agent’s genome under selective pressure, resulting in substantially more efficient training. In this case efficiency is the production of superior competitive ability at a lower evolutionary velocity. Prisoner’s dilemma playing agents are evolved for 6400 generations, taking samples at eight exponentially-spaced epochs. This permits assessment of the change in populations over long evolutionary time. Agen...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Daniel A. Ashlock, Eun-Youn Kim, Wendy Ashlock
• Keywords: Artificial Intelligence, CEC 2007, Evolutionary Velocity, Noise Level, Prisoner’s Dilemma