Experimental criteria to identify efficient probabilistic memory-one strategies for the iterated prisoner’s dilemma

Philippe Mathieu (1, 2, 3) , Jean-Paul Delahaye (1, 2, 3)

1 SMAC - Systèmes Multi-Agents et Comportements
2 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
3 Université de Lille

Many works and articles about probabilistic strategies for the prisoner's dilemma have already been realised. Notably Press & Dyson 2012 article has lead to renewed interest in the subject. In this article, with the help of a systematic study of probabilistic memory-one strategies, we show that there is a basic criterion to configure and anticipate their success. This criterion, identified through the study of large homogeneous sets of strategies, is then compared to other similar criteria. Our experimental method has allowed us to discover new strategies that are efficient not only in probabilistic environments, but also in more general, probabilistic or non-probabilistic environments. We test the robustness of our results by various methods and compare the new strategies obtained with the best strategies currently known.

Mots clés: Iterated prisoner's dilemma; probabilistic strategies; Simulation; Agents' strategies; Evolutionary game theory; Behaviour * Corresponding author

Domaines: Système multi-agents [cs.MA]; Modélisation et simulation; Intelligence artificielle [cs.AI]

Philippe Mathieu, Jean-Paul Delahaye. Experimental criteria to identify efficient probabilistic memory-one strategies for the iterated prisoner’s dilemma. Simulation Modelling Practice and Theory, 2019, pp.101946. ⟨10.1016/j.simpat.2019.101946⟩. ⟨hal-02175088⟩