Strategies for the Iterated Prisoner's Dilemma

TL;DR

This paper investigates various strategies for the Iterated Prisoner's Dilemma, emphasizing Tit-For-Tat, correcting bounds for zero-determinant strategies, and evaluating their performance in tournaments.

Contribution

It provides a theoretical correction for zero-determinant strategies and introduces a new player inspired by Markov Decision Processes.

Findings

Tit-For-Tat strategies are significant in evolutionary game theory

Corrected bounds for zero-determinant strategies are presented

New Markov Decision Process-inspired strategy performs well in tournaments

Abstract

We explore some strategies which tend to perform well in the IPD. We start off by showing the significance of Tit-For-Tat strategies in evolutionary game theory. This is followed by a theoretical derivation of zero-determinant strategies, where we highlight an error on bounds for scale parameters from the original paper on ZD strategies[6]. We then present examples of such strategies and create a custom player drawing inspiration from Markov Decision Processes. At the end we pit them all against each other and see how they perform in an IPD tournament.