This paper focuses on the Noisy Iterated Prisoner's Dilemma, a version of the Iterated Prisoner's Dilemma (IPD) in which there is a nonzero probability that a "cooperate" action will accidentally be changed into a "defect" action and vice versa. Tit-For-Tat and other strategies that do quite well in the ordinary (non-noisy) IPD can do quite badly in the Noisy IPD. This paper presents a technique called symbolic noise detection, for detecting whether anomalies in player's behavior are deliberate or accidental. The key idea is to construct a model of the other agent's behavior, and watch for any deviation from this model. If the other agent's next action is inconsistent with this model, the inconsistency can be due either to noise or to a genuine change in their behavior; and we can often distinguish between two cases by waiting to see whether this inconsistency persists in next few moves. We entered several different versions of our strategy...
Tsz-Chiu Au, Dana S. Nau