3 citations · 3 across the 7 of their papers we have counts for
9 papers
Limiting-Kernel Q(): Bridging Short and Long Horizons
Tolga Ok, Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani +1
In reinforcement learning, more accurate policy evaluation has been frequently shown to improve downstream policy optimization performance. For tractability, most value estimators…
Benign Geometry and Distributional Robustness of Synthesis
Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani, Tamás Keviczky +1
In this paper, we study standard and distributionally robust synthesis problem of a stabilizing state-feedback controller for discrete-time linear time-invariant sy…
Control and Reinforcement Learning through the Lens of Optimization: An Algorithmic Perspective
Tolga Ok, Arman Sharifi Kolarijani, Mohamad Amin Sharif Kolarijani +1
The connection between control algorithms for Markov decision processes and optimization algorithms has been implicitly and explicitly exploited since the introduction of dynamic p…
Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani +1
In this paper, we provide a novel algorithm for solving planning and learning problems of Markov decision processes. The proposed algorithm follows a policy iteration-type update b…
Adaptive Composite Online Optimization: Predictions in Static and Dynamic Environments
Pedro Zattoni Scroccaro, Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani
In the past few years, Online Convex Optimization (OCO) has received notable attention in the control literature thanks to its flexible real-time nature and powerful performance gu…
Multimode Diagnosis for Switched Affine Systems with Noisy Measurement
Jingwei Dong, Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani
We study a diagnosis scheme to reliably detect the active mode of discrete-time, switched affine systems in the presence of measurement noise and asynchronous switching. The propos…
A Decentralized Event-Based Approach for Robust Model Predictive Control
Arman Sharifi Kolarijani, Sander Bregman, Peyman Mohajerin Esfahani +1
In this paper, we propose an event-based sampling policy to implement a constraint-tightening, robust MPC method. The proposed policy enjoys a computationally tractable design and…
Continuous-Time Accelerated Methods via a Hybrid Control Lens
Arman Sharifi Kolarijani, Peyman Mohajerin Esfahani, Tamás Keviczky
Treating optimization methods as dynamical systems can be traced back centuries ago in order to comprehend the notions and behaviors of optimization methods. Lately, this mind set…
Technical Report: Timing Abstraction of Perturbed LTI systems with -based Event-Triggering Mechanism
Arman Sharifi Kolarijani, Manuel Mazo, Tamas Keviczky
In networked control systems, the advent of event-triggering strategies in the sampling process has resulted in the usage reduction of network capacities, such as communication ban…