3 citations · 3 across the 6 of their papers we have counts for
6 papers
Policy Iteration for Domain Randomized Linear Quadratic Systems
Abbas Pasdar, Farnaz Adib Yaghmaie
In this work, we study policy optimization under domain randomization for linear quadratic control, focusing on learning a single state-feedback controller that minimizes the avera…
Direct Data Driven Natural Gradient Descent for Control
Ramin Esmzad, Farnaz Adib Yaghmaie, Bahare Kiumarsi +1
This paper introduces a novel direct data-driven control framework based on Natural Gradient Descent (NGD) to design interpretable and robust closed-loop policies without requiring…
Consensus and Synchronization of Multi-agent Systems over Finite Fields - Graph Topologies
Kristian Hengster-Movrić, Šimon Lehký, Farnaz Adib Yaghmaie
This paper presents cooperative protocols for multi-agent systems with agents having a finite state-space. Both scalar single-integrator consensus and general LTI system synchroniz…
Convergence of Flow-Policy Gradient Learning for Linear Quadratic Regulator Problems
Farnaz Adib Yaghmaie, Arunava Naha
Flow -learning has recently been introduced to integrate learning from expert demonstrations into an actor-critic structure. Central to this innovation is the ``the one-step pol…
Natural Gradient Descent for Control
Ramin Esmzad, Farnaz Adib Yaghmaie, Hamidreza Modares
This paper bridges optimization and control, and presents a novel closed-loop control framework based on natural gradient descent, offering a trajectory-oriented alternative to tra…
A Crash Course on Reinforcement Learning
Farnaz Adib Yaghmaie, Lennart Ljung
The emerging field of Reinforcement Learning (RL) has led to impressive results in varied domains like strategy games, robotics, etc. This handout aims to give a simple introductio…