4 papers
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-MovriÄ, Å imon Lehký, Farnaz Adib Yaghmaie
This paper brings cooperative protocols for multi-agent systems with agents having a finite state-space. Both scalar single-integrator consensus and general LTI systems synchroniza…
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…