b'John Lygeros'

research

∙ 04/24/2023

Stochastic MPC for energy hubs using data driven demand forecasting

Energy hubs convert and distribute energy resources by combining differe...

0 Francesco Micheli, et al. ∙

research

∙ 04/24/2023

Designing Optimal Personalized Incentive for Traffic Routing using BIG Hype algorithm

We study the problem of optimally routing plug-in electric and conventio...

0 Panagiotis D. Grontas, et al. ∙

research

∙ 02/09/2023

Designing Fairness in Autonomous Peer-to-peer Energy Trading

Several autonomous energy management and peer-to-peer trading mechanisms...

0 Varsha Behrunani, et al. ∙

research

∙ 11/18/2022

Optimal service station design for traffic mitigation via genetic algorithm and neural network

This paper analyzes how the presence of service stations on highways aff...

0 Carlo Cenedese, et al. ∙

research

∙ 11/15/2022

Drone-based Volume Estimation in Indoor Environments

Volume estimation in large indoor spaces is an important challenge in ro...

0 Samuel Balula, et al. ∙

research

∙ 11/14/2022

Implications of Regret on Stability of Linear Dynamical Systems

The setting of an agent making decisions under uncertainty and under dyn...

0 Aren Karapetyan, et al. ∙

research

∙ 11/14/2022

Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control

We consider control of dynamical systems through the lens of competitive...

0 Andrea Martin, et al. ∙

research

∙ 11/14/2022

Stability and Robustness of Distributed Suboptimal Model Predictive Control

In distributed model predictive control (MPC), the control input at each...

0 Giuseppe Belgioioso, et al. ∙

research

∙ 05/31/2022

Data-driven Reference Trajectory Optimization for Precision Motion Systems

We propose an optimization-based method to improve contour tracking perf...

0 Samuel Balula, et al. ∙

research

∙ 05/24/2022

Advanced Manufacturing Configuration by Sample-efficient Batch Bayesian Optimization

We propose a framework for the configuration and operation of expensive-...

0 Xavier Guidetti, et al. ∙

research

∙ 04/10/2022

Regret Analysis of Online Gradient Descent-based Iterative Learning Control with Model Mismatch

In Iterative Learning Control (ILC), a sequence of feedforward control a...

0 Efe C. Balta, et al. ∙

research

∙ 02/01/2022

PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation

Despite their success, policy gradient methods suffer from high variance...

0 Matilde Gargiani, et al. ∙

research

∙ 12/31/2021

Stochastic convex optimization for provably efficient apprenticeship learning

We consider large-scale Markov decision processes (MDPs) with an unknown...

0 Angeliki Kamoutsi, et al. ∙

research

∙ 12/28/2021

Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations

We consider large-scale Markov decision processes with an unknown cost f...

0 Angeliki Kamoutsi, et al. ∙

research

∙ 10/29/2021

Physics-informed linear regression is a competitive approach compared to Machine Learning methods in building MPC

Because physics-based building models are difficult to obtain as each bu...

0 Felix Bünning, et al. ∙

research

∙ 03/25/2021

Sample-efficient Plasma Spray Process Configuration with Constrained Bayesian Optimization

Recent work has shown constrained Bayesian optimization to be a powerful...

0 Xavier Guidetti, et al. ∙

research

∙ 01/19/2021

Safe and Efficient Model-free Adaptive Control via Bayesian Optimization

Adaptive control approaches yield high-performance controllers when a pr...

0 Christopher König, et al. ∙

research

∙ 11/26/2020

Learning from Simulation, Racing in Reality

We present a reinforcement learning-based solution to autonomously race ...

0 Eugenio Chisari, et al. ∙

research

∙ 11/26/2020

Input Convex Neural Networks for Building MPC

Model Predictive Control in buildings can significantly reduce their ene...

0 Felix Bünning, et al. ∙

research

∙ 03/10/2020

Optimization-Based Hierarchical Motion Planning for Autonomous Racing

In this paper we propose a hierarchical controller for autonomous racing...

0 José L. Vázquez, et al. ∙

research

∙ 10/01/2019

The Nash Equilibrium with Inertia in Population Games

In the traditional game-theoretic set up, where agents select actions an...

0 Basilio Gentile, et al. ∙

research

∙ 05/13/2019

AMZ Driverless: The Full Autonomous Racing System

This paper presents the algorithms and system architecture of an autonom...

0 Juraj Kabzan, et al. ∙

research

∙ 11/22/2018

Inference of the three-dimensional chromatin structure and its temporal behavior

Understanding the three-dimensional (3D) structure of the genome is esse...

0 Bianca-Cristina Cristescu, et al. ∙

research

∙ 03/20/2018

Decentralized decision making for networks of uncertain systems

Distributed model predictive control (MPC) has been proven a successful ...

0 Georgios Darivianakis, et al. ∙

research

∙ 03/20/2018

Distributed Model Predictive Control for Linear Systems with Adaptive Terminal Sets

In this paper, we propose a distributed model predictive control (DMPC) ...

0 Georgios Darivianakis, et al. ∙

research

∙ 03/07/2018

On the Efficiency of Nash Equilibria in Aggregative Charging Games

Several works have recently suggested to model the problem of coordinati...

0 Dario Paccagnan, et al. ∙

research

∙ 03/07/2018

On the Efficiency of Nash Equilibria in Charging Games

We consider charging problems, where the goal is to coordinate the charg...

0 Dario Paccagnan, et al. ∙

research

∙ 12/11/2017

A Non-Cooperative Game Approach to Autonomous Racing

We consider autonomous racing of two cars and present an approach to for...

0 Alexander Liniger, et al. ∙

research

∙ 06/14/2017

A distributed algorithm for average aggregative games with coupling constraints

We consider the framework of average aggregative games, where the cost f...

0 Francesca Parise, et al. ∙

John Lygeros

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