5 citations · 5 across the 8 of their papers we have counts for
9 papers
Decentralized Optimal Equilibrium Learning Over Dynamic Networks
Seref Taha Kiremitci, Muhammed O. Sayin
This paper studies decentralized learning of socially optimal equilibria in finite normal-form games over dynamic communication networks. Each agent observes only its own realized…
Decentralized Optimal Equilibrium Learning in Stochastic Games via Single-bit Feedback
Seref Taha Kiremitci, Ahmed Said Donmez, Muhammed O. Sayin
We study decentralized equilibrium selection in stochastic games under severe information and communication constraints. In such settings, convergence to equilibrium alone is insuf…
Actor-Dual-Critic Dynamics for Zero-sum and Identical-Interest Stochastic Games
Ahmed Said Donmez, Yuksel Arslantas, Muhammed O. Sayin
We propose a novel independent and payoff-based learning framework for stochastic games that is model-free, game-agnostic, and gradient-free. The learning dynamics follow a best-re…
Omniscient Attacker in Stochastic Security Games with Interdependent Nodes
Yuksel Arslantas, Ahmed Said Donmez, Ege Yuceel +1
The adoption of reinforcement learning for critical infrastructure defense introduces a vulnerability where sophisticated attackers can strategically exploit the defense algorithm'…
Controlling Traffic without Tolls: A Non-Monetary Framework for Autonomous Intersections
Arda Kosay, Yusuf Saltan, Jyun-Jhe Wang +2
The increasing complexity of urban transportation systems, driven by connected and automated vehicles, calls for new modeling paradigms and scalable control strategies. We propose…
Achieving Pareto Optimality in Games via Single-bit Feedback
Seref Taha Kiremitci, Ahmed Said Donmez, Muhammed O. Sayin
Efficient coordination in multi-agent systems often incurs high communication overhead or slow convergence rates, making scalable welfare optimization difficult. We propose Single-…
Generalized Individual Q-learning for Polymatrix Games with Partial Observations
Ahmed Said Donmez, Muhammed O. Sayin
This paper addresses the challenge of limited observations in non-cooperative multi-agent systems where agents can have partial access to other agents' actions. We present the gene…
Strategizing against Q-learners: A Control-theoretical Approach
Yuksel Arslantas, Ege Yuceel, Muhammed O. Sayin
In this paper, we explore the susceptibility of the independent Q-learning algorithms (a classical and widely used multi-agent reinforcement learning method) to strategic manipulat…
Team-Fictitious Play for Reaching Team-Nash Equilibrium in Multi-team Games
Ahmed Said Donmez, Yuksel Arslantas, Muhammed O. Sayin
Multi-team games, prevalent in robotics and resource management, involve team members striving for a joint best response against other teams. Team-Nash equilibrium (TNE) predicts t…