193 citations · 703 across the 59 of their papers we have counts for
70 papers
Functional role of synchronization: A mean-field control perspective
Prashant Mehta, Sean Meyn
The broad goal of the research surveyed in this article is to develop methods for understanding the aggregate behavior of interconnected dynamical systems, as found in mathematical…
Interacting Particle Systems for Fast Linear Quadratic RL
Anant A Joshi, Heng-Sheng Chang, Amirhossein Taghvaei +2
This paper is concerned with the design of algorithms based on systems of interacting particles to represent, approximate, and learn the optimal control law for reinforcement learn…
Dual Ensemble Kalman Filter for Stochastic Optimal Control
Anant A. Joshi, Amirhossein Taghvaei, Prashant G. Mehta +1
In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of rein…
Convex Q Learning in a Stochastic Environment: Extended Version
Fan Lu, Sean Meyn
The paper introduces the first formulation of convex Q-learning for Markov decision processes with function approximation. The algorithms and theory rest on a relaxation of a dual…
The case for and against fixed step-size: Stochastic approximation algorithms in optimization and machine learning
Caio Kalil Lauand, Ioannis Kontoyiannis, Sean Meyn
Theory and application of stochastic approximation (SA) have become increasingly relevant due in part to applications in optimization and reinforcement learning. This paper takes a…
Stability of Q-Learning Through Design and Optimism
Sean Meyn
Q-learning has become an important part of the reinforcement learning toolkit since its introduction in the dissertation of Chris Watkins in the 1980s. The purpose of this paper is…