3 papers
eess.SY2025
Almost Sure Convergence of Networked Policy Gradient over Time-Varying Networks in Markov Potential Games
Sarper Aydin, Ceyhun Eksin
We propose networked policy gradient play for solving Markov potential games with continuous and/or discrete state-action pairs. During the game, agents use parametrized and differ…
math.OC2025
The Lagrangian Method for Solving Constrained Markov Games
Soham Das, Santiago Paternain, Luiz F. O. Chamon +1
We propose the concept of a Lagrangian game to solve constrained Markov games. Such games model scenarios where agents face cost constraints in addition to their individual rewards…
cs.AI2024
Simulation-Based Optimistic Policy Iteration For Multi-Agent MDPs with Kullback-Leibler Control Cost
Khaled Nakhleh, Ceyhun Eksin, Sabit Ekin
This paper proposes an agent-based optimistic policy iteration (OPI) scheme for learning stationary optimal stochastic policies in multi-agent Markov Decision Processes (MDPs), in…