90 citations · 910 across the 140 of their papers we have counts for
36 papers · 1 filter
Reinforcement Learning to Accelerate Primal-Dual Hybrid Gradient for Linear Programming
Jinhwan Sul, Alex Oshin, Evangelos A. Theodorou
Primal-dual hybrid gradient (PDHG) methods solve large-scale linear programs (LPs) using GPU-friendly matrix-vector products and projections, but their practical performance depend…
Scalable Deep Unfolding of Conic Optimizers
Alex Oshin, Rahul Vodeb Ghosh, Evangelos A. Theodorou
Deep unfolding (DU) accelerates iterative optimizers by introducing learnable components and training them through unrolled iterations, but extending DU to the large-scale semidefi…
Fundamental Limits for Sensor-Based Control via the Gibbs Variational Principle
Vincent Pacelli, Evangelos A. Theodorou
Fundamental limits on the performance of feedback controllers are essential for benchmarking algorithms, guiding sensor selection, and certifying task feasibility -- yet few genera…
Deep FlexQP: Accelerated Nonlinear Programming via Deep Unfolding
Alex Oshin, Rahul Vodeb Ghosh, Augustinos D. Saravanos +1
We propose FlexQP, an always-feasible convex quadratic programming (QP) solver based on an elastic relaxation of the QP constraints. If the original constraints are feasib…
Distributed Stochastic Search for Multi-Agent Model Predictive Control
Taehyun Yoon, Augustinos D. Saravanos, Evangelos A. Theodorou
Many real-world multi-agent systems exhibit nonlinear dynamics and complex inter-agent interactions. As these systems increase in scale, the main challenges arise from achieving sc…
Scaling Robust Optimization for Swarms: A Distributed Perspective
Arshiya Taj Abdul, Augustinos D. Saravanos, Evangelos A. Theodorou
This article introduces a decentralized robust optimization framework for safe multi-agent control under uncertainty. Although stochastic noise has been the primary form of modelin…
Deep Distributed Optimization for Large-Scale Quadratic Programming
Augustinos D. Saravanos, Hunter Kuperman, Alex Oshin +3
Quadratic programming (QP) forms a crucial foundation in optimization, encompassing a broad spectrum of domains and serving as the basis for more advanced algorithms. Consequently,…
Second-Order Stein Variational Dynamic Optimization
Yuichiro Aoyama, Peter Lehmamnn, Evangelos A. Theodorou
We present a novel second-order trajectory optimization algorithm based on Stein Variational Newton's Method and Maximum Entropy Differential Dynamic Programming. The proposed algo…
Second-Order Constrained Dynamic Optimization
Yuichiro Aoyama, Oswin So, Augustinos D. Saravanos +1
This paper provides an overview, analysis, and comparison of second-order dynamic optimization algorithms, i.e., constrained Differential Dynamic Programming (DDP) and Sequential Q…
Generalized Maximum Entropy Differential Dynamic Programming
Yuichiro Aoyama, Evangelos A. Theodorou
We present a sampling-based trajectory optimization method derived from the maximum entropy formulation of Differential Dynamic Programming with Tsallis entropy. This method is a g…
Differentiable Robust Model Predictive Control
Alex Oshin, Hassan Almubarak, Evangelos A. Theodorou
Deterministic model predictive control (MPC), while powerful, is often insufficient for effectively controlling autonomous systems in the real-world. Factors such as environmental…
Optimal Control of Granular Material
Yuichiro Aoyama, Amin Haeri, Evangelos A. Theodorou
The control of granular materials, showing up in many industrial applications, is a challenging open research problem. Granular material systems are complex-behavior (as they could…
Sampling-Based Optimization for Multi-Agent Model Predictive Control
Ziyi Wang, Augustinos D. Saravanos, Hassan Almubarak +2
We systematically review the Variational Optimization, Variational Inference and Stochastic Search perspectives on sampling-based dynamic optimization and discuss their connections…
Solving Feynman-Kac Forward Backward SDEs Using McKean-Markov Branched Sampling
Kelsey P. Hawkins, Ali Pakniyat, Evangelos Theodorou +1
We propose a new method for the numerical solution of the forward-backward stochastic differential equations (FBSDE) appearing in the Feynman-Kac representation of the value functi…
Parameterized Differential Dynamic Programming
Alex Oshin, Matthew D. Houghton, Michael J. Acheson +2
Differential Dynamic Programming (DDP) is an efficient trajectory optimization algorithm relying on second-order approximations of a system's dynamics and cost function, and has re…
Opinion Dynamics Steering using Stochastic Search
Ziyi Wang, Evangelos A. Theodorou
In this paper, we apply the stochastic search dynamic optimization framework for steering opinion dynamics in a partially active population. The framework is grounded on stochastic…
Multimodal Maximum Entropy Dynamic Games
Oswin So, Kyle Stachowicz, Evangelos A. Theodorou
Environments with multi-agent interactions often result a rich set of modalities of behavior between agents due to the inherent suboptimality of decision making processes when agen…
Constrained Covariance Steering Based Tube-MPPI
Isin M. Balci, Efstathios Bakolas, Bogdan Vlahov +1
In this paper, we present a new trajectory optimization algorithm for stochastic linear systems which combines Model Predictive Path Integral (MPPI) control with Constrained Covari…
Maximum Entropy Differential Dynamic Programming
Oswin So, Ziyi Wang, Evangelos A. Theodorou
In this paper, we present a novel maximum entropy formulation of the Differential Dynamic Programming algorithm and derive two variants using unimodal and multimodal value function…
Spatio-Temporal Differential Dynamic Programming for Control of Fields
Ethan N. Evans, Oswin So, Andrew P. Kendall +2
We consider the optimal control problem of a general nonlinear spatio-temporal system described by Partial Differential Equations (PDEs). Theory and algorithms for control of spati…
Receding Horizon Differential Dynamic Programming Under Parametric Uncertainty
Yuichiro Aoyama, Augustinos D. Saravanos, Evangelos A. Theodorou
Generalized Polynomial Chaos (gPC) theory has been widely used for representing parametric uncertainty in a system, thanks to its ability to propagate uncertainty evolution. In an…
Open-loop Deterministic Density Control of Marked Jump Diffusions
Kaivlaya Bakshi, Evangelos A. Theodorou
The standard practice in modeling dynamics and optimal control of a large population, ensemble, multi-agent system represented by it's continuum density, is to model individual dec…
Adaptive Risk Sensitive Model Predictive Control with Stochastic Search
Ziyi Wang, Oswin So, Keuntaek Lee +2
We present a general framework for optimizing the Conditional Value-at-Risk for dynamical systems using stochastic search. The framework is capable of handling the uncertainty from…
Forward-Backward Rapidly-Exploring Random Trees for Stochastic Optimal Control
Kelsey P. Hawkins, Ali Pakniyat, Evangelos Theodorou +1
We propose a numerical method for the computation of the forward-backward stochastic differential equations (FBSDE) appearing in the Feynman-Kac representation of the value functio…