Abstract-The motivation of this work is to investigate the classic problem of the Iterated Prisoner's Dilemma in an environment with many players with different behaviors. We review previous analysis of the tournaments proposed by Robert Axelrod, focusing primarily on the strategies adopted by their players. These agents have been recreated in this new tournament, based on the information available, and several others were included, from periodically non-rational agents to agents based on modern paradigms such as neural networks, genetic algorithms, reinforcement learning, trackers, etc. This gives heterogeneous and rich alternatives to the basic tournament. As a result, we verified the classification of these players for various game modes (variation of maximum number of iterations), and analyze their performance based on this criterion.