Limiting dynamics for Q-learning with memory one in symmetric two-player, two-action games
Dynamical Systems
2022-10-04 v2 Adaptation and Self-Organizing Systems
Abstract
We develop a method based on computer algebra systems to represent the mutual pure strategy best-response dynamics of symmetric two-player, two-action repeated games played by players with a one-period memory. We apply this method to the iterated prisoner's dilemma, stag hunt and hawk-dove games and identify all possible equilibrium strategy pairs and the conditions for their existence. The only equilibrium strategy pair that is possible in all three games is the win-stay, lose-shift strategy. Lastly, we show that the mutual best-response dynamics are realized by a sample batch Q-learning algorithm in the infinite batch size limit.
Keywords
Cite
@article{arxiv.2107.13995,
title = {Limiting dynamics for Q-learning with memory one in symmetric two-player, two-action games},
author = {Janusz M Meylahn and Lars Janssen},
journal= {arXiv preprint arXiv:2107.13995},
year = {2022}
}
Comments
30 pages, 12 figures