Search Results for author:
Found 2 papers, 0 papers with code
Learning in quantum games
In this paper, we introduce a class of learning dynamics for general quantum games, that we call "follow the quantum regularized leader" (FTQL), in reference to the classical "follow the regularized leader" (FTRL) template for learning in finite games.
On the convergence of policy gradient methods to Nash equilibria in general stochastic games
Learning in stochastic games is a notoriously difficult problem because, in addition to each other's strategic decisions, the players must also contend with the fact that the game itself evolves over time, possibly in a very complicated manner.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
