181 citations · 321 across the 23 of their papers we have counts for
26 papers
Convergence of Heterogeneous Learning Dynamics in Zero-sum Stochastic Games
Yuksel Arslantas, Ege Yuceel, Yigit Yalin +1
This paper presents new families of algorithms for the repeated play of two-agent (near) zero-sum games and two-agent zero-sum stochastic games. For example, the family includes fi…
Finite-horizon Approximations and Episodic Equilibrium for Stochastic Games
Muhammed O. Sayin
This paper proposes a finite-horizon approximation scheme and introduces episodic equilibrium as a solution concept for stochastic games (SGs), where agents strategize based on the…
Episodic Logit-Q Dynamics for Efficient Learning in Stochastic Teams
Onur Unlu, Muhammed O. Sayin
We present new learning dynamics combining (independent) log-linear learning and value iteration for stochastic games within the auxiliary stage game framework. The dynamics presen…
Logit-Q Dynamics for Efficient Learning in Stochastic Teams
Ahmed Said Donmez, Onur Unlu, Muhammed O. Sayin
We present a new family of logit-Q dynamics for efficient learning in stochastic games by combining the log-linear learning (also known as logit dynamics) for the repeated play of…
Fictitious Play in Markov Games with Single Controller
Muhammed O. Sayin, Kaiqing Zhang, Asuman Ozdaglar
Certain but important classes of strategic-form games, including zero-sum and identical-interest games, have the fictitious-play-property (FPP), i.e., beliefs formed in fictitious…
Episodic Logit-Q Dynamics for Efficient Learning in Stochastic Teams
Onur Unlu, Muhammed O. Sayin
We present new learning dynamics combining (independent) log-linear learning and value iteration for stochastic games within the auxiliary stage game framework. The dynamics presen…
On the Global Convergence of Stochastic Fictitious Play in Stochastic Games with Turn-based Controllers
Muhammed O. Sayin
This paper presents a learning dynamic with almost sure convergence guarantee for any stochastic game with turn-based controllers (on state transitions) as long as stage-payoffs in…
On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games
Muhammed O. Sayin, K. Alperen Cetiner
We analyze the convergence properties of the two-timescale fictitious play combining the classical fictitious play with the Q-learning for two-player zero-sum stochastic games with…
Independent Learning in Stochastic Games
Asuman Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang
Reinforcement learning (RL) has recently achieved tremendous successes in many artificial intelligence applications. Many of the forefront applications of RL involve multiple agent…
Decentralized Q-Learning in Zero-sum Markov Games
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie +2
We study multi-agent reinforcement learning (MARL) in infinite-horizon discounted zero-sum Markov games. We focus on the practical but challenging setting of decentralized MARL, wh…
Fictitious play in zero-sum stochastic games
Muhammed O. Sayin, Francesca Parise, Asuman Ozdaglar
We present a novel variant of fictitious play dynamics combining classical fictitious play with Q-learning for stochastic games and analyze its convergence properties in two-player…
Bayesian Persuasion with State-Dependent Quadratic Cost Measures
Muhammed O. Sayin, Tamer Basar
We address Bayesian persuasion between a sender and a receiver with state-dependent quadratic cost measures for general classes of distributions. The receiver seeks to make mean-sq…
Deception-As-Defense Framework for Cyber-Physical Systems
Muhammed O. Sayin, Tamer Basar
We introduce deceptive signaling framework as a new defense measure against advanced adversaries in cyber-physical systems. In general, adversaries look for system-related informat…
Reliable Smart Road Signs
Muhammed O. Sayin, Chung-Wei Lin, Eunsuk Kang +2
In this paper, we propose a game theoretical adversarial intervention detection mechanism for reliable smart road signs. A future trend in intelligent transportation systems is ``s…
Persuasion-based Robust Sensor Design Against Attackers with Unknown Control Objectives
Muhammed O. Sayin, Tamer Basar
In this paper, we introduce a robust sensor design framework to provide "persuasion-based" defense in stochastic control systems against an unknown type attacker with a control obj…
Reliable Intersection Control in Non-cooperative Environments
Muhammed O. Sayin, Chung-Wei Lin, Shinichi Shiraishi +1
We propose a reliable intersection control mechanism for strategic autonomous and connected vehicles (agents) in non-cooperative environments. Each agent has access to his/her earl…
Secure Sensor Design Against Undetected Infiltration: Minimum Impact-Minimum Damage
Muhammed O. Sayin, Tamer Başar
We propose a new defense mechanism against undetected infiltration into controllers in cyber-physical systems. To this end, we cautiously design the outputs of the sensors that mon…
Team-Optimal Distributed MMSE Estimation in General and Tree Networks
Muhammed O. Sayin, Suleyman S. Kozat, Tamer Başar
We construct team-optimal estimation algorithms over distributed networks for state estimation in the finite-horizon mean-square error (MSE) sense. Here, we have a distributed coll…
Hierarchical Multistage Gaussian Signaling Games in Noncooperative Communication and Control Systems
Muhammed O. Sayin, Emrah Akyol, Tamer Basar
We analyze in this paper finite horizon hierarchical signaling games between (information provider) senders and (decision maker) receivers in a dynamic environment. The underlying…
On the Structure of Equilibrium Strategies in Dynamic Gaussian Signaling Games
Muhammed Sayin, Emrah Akyol, Tamer Basar
This paper analyzes a finite horizon dynamic signaling game motivated by the well-known strategic information transmission problems in economics. The mathematical model involves in…
A new robust adaptive algorithm for underwater acoustic channel equalization
Dariush Kari, Muhammed Omer Sayin, Suleyman Serdar Kozat
We introduce a novel family of adaptive robust equalizers for highly challenging underwater acoustic (UWA) channel equalization. Since the underwater environment is highly non-stat…
Stochastic Subgradient Algorithms for Strongly Convex Optimization over Distributed Networks
N. Denizcan Vanli, Muhammed O. Sayin, Suleyman S. Kozat
We study diffusion and consensus based optimization of a sum of unknown convex objective functions over distributed networks. The only access to these functions is through stochast…
Compressive Diffusion Strategies Over Distributed Networks for Reduced Communication Load
Muhammed O. Sayin, Suleyman S. Kozat
We study the compressive diffusion strategies over distributed networks based on the diffusion implementation and adaptive extraction of the information from the compressed diffusi…
Predicting Nearly As Well As the Optimal Twice Differentiable Regressor
N. Denizcan Vanli, Muhammed O. Sayin, Suleyman S. Kozat
We study nonlinear regression of real valued data in an individual sequence manner, where we provide results that are guaranteed to hold without any statistical assumptions. We add…