37 citations · 58 across the 10 of their papers we have counts for
11 papers
Fictitious Play in Extensive-Form Games of Imperfect Information
Jason Castiglione, Gürdal Arslan
We study the long-term behavior of the fictitious play process in repeated extensive-form games of imperfect information with perfect recall. Each player maintains incorrect belief…
General-Sum Markov Games with Borel Spaces: Existence of Approximate Nash Equilibria via Finite Model Approximations under Setwise or Weak Continuity
Naci Saldi, Gurdal Arslan, Serdar Yuksel
Establishing the existence of exact or near Markov or stationary perfect Nash equilibria in nonzero-sum Markov games over Borel spaces is a challenging problem with limited positiv…
Subjective Equilibria under Beliefs of Exogenous Uncertainty: Linear Quadratic Case
Gürdal Arslan, Serdar Yüksel
We consider a stochastic dynamic game where players have their own linear state dynamics and quadratic cost functions. Players are coupled through some environment variables, gener…
Satisficing Paths to Equilibrium, Generalized Weakly Acyclic Games, and Learning
Bora Yongacoglu, Gwendolen Hickey, Gürdal Arslan +2
Weakly acyclic games generalize potential games and have shown to be fundamental in the study of multi-agent learning as they allow for convergence to an equilibrium via best-respo…
Paths to Equilibrium in Games
Bora Yongacoglu, Gürdal Arslan, Lacra Pavel +1
In multi-agent reinforcement learning (MARL) and game theory, agents repeatedly interact and revise their strategies as new data arrives, producing a sequence of strategy profiles.…
Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence
Bora Yongacoglu, Gürdal Arslan, Serdar Yüksel
Non-stationarity is a fundamental challenge in multi-agent reinforcement learning (MARL), where agents update their behaviour as they learn. Many theoretical advances in MARL avoid…
Mean-Field Games With Finitely Many Players: Independent Learning and Subjectivity
Bora Yongacoglu, Gürdal Arslan, Serdar Yüksel
Independent learners are agents that employ single-agent algorithms in multi-agent systems, intentionally ignoring the effect of other strategic agents. This paper studies mean-fie…
Satisficing Paths and Independent Multi-Agent Reinforcement Learning in Stochastic Games
Bora Yongacoglu, Gürdal Arslan, Serdar Yüksel
In multi-agent reinforcement learning (MARL), independent learners are those that do not observe the actions of other agents in the system. Due to the decentralization of informati…
Subjective Equilibria under Beliefs of Exogenous Uncertainty for Dynamic Games
Gürdal Arslan, Serdar Yüksel
We present a subjective equilibrium notion (called "subjective equilibrium under beliefs of exogenous uncertainty (SEBEU)" for stochastic dynamic games in which each player chooses…
Decentralized Learning for Optimality in Stochastic Dynamic Teams and Games with Local Control and Global State Information
Bora Yongacoglu, Gürdal Arslan, Serdar Yüksel
Stochastic dynamic teams and games are rich models for decentralized systems and challenging testing grounds for multi-agent learning. Previous work that guaranteed team optimality…
Decentralized Q-Learning for Stochastic Teams and Games
Gürdal Arslan, Serdar Yüksel
There are only a few learning algorithms applicable to stochastic dynamic teams and games which generalize Markov decision processes to decentralized stochastic control problems in…