38 citations · 97 across the 57 of their papers we have counts for
29 papers · 1 filter
Model-Based Reinforcement Learning Under Confounding
Nishanth Venkatesh, Andreas A. Malikopoulos
We investigate model-based reinforcement learning in contextual Markov decision processes (C-MDPs) in which the context is unobserved and induces confounding in the offline dataset…
A Hybrid Physics-Based and Reinforcement Learning Framework for Electric Vehicle Charging Time Prediction
Praharshitha Aryasomayajula, Ting Bai, Andreas A. Malikopoulos
In this paper, we develop a hybrid prediction framework for accurate electric vehicle (EV) charging time estimation, a capability that is critical for trip planning, user satisfact…
Optimal Platoon Formation and Stable Benefit Allocation in Mixed-Energy Truck Fleets under Size Limitations
Ting Bai, Xinfeng Ru, Andreas A. Malikopoulos
In this paper, we investigate cooperative platoon formation and benefit allocation in mixed-energy truck fleets composed of both electric and fuel-powered trucks. The central chall…
Game-Theoretic Learning-Based Mitigation of Insider Threats
Gehui Xu, Kaiwen Chen, Thomas Parisini +1
An insider is defined as a team member who covertly deviates from the team's optimal collaborative control strategy in pursuit of a private objective, while maintaining an outward…
Learning-Based Robust Bayesian Persuasion with Conformal Prediction Guarantees
Heeseung Bang, Andreas A. Malikopoulos
Classical Bayesian persuasion assumes that senders fully understand how receivers form beliefs and make decisions--an assumption that rarely holds when receivers possess private in…
Accelerating Time-Optimal Trajectory Planning for Connected and Automated Vehicles with Graph Neural Networks
Viet-Anh Le, Andreas A. Malikopoulos
In this paper, we present a learning-based framework that accelerates time- and energy-optimal trajectory planning for connected and automated vehicles (CAVs) using graph neural ne…
Actor-Critic Learning for Risk-Constrained Linear Quadratic Regulation
Weijian Li, Andreas A. Malikopoulos
In this paper, we investigate the infinite-horizon risk-constrained linear quadratic regulator problem (RC-QR), which augments the classical LQR formulation with a statistical cons…
A Communication-Efficient Decentralized Actor-Critic Algorithm
Xiaoxing Ren, Nicola Bastianello, Thomas Parisini +1
In this paper, we study the problem of reinforcement learning in multi-agent systems where communication among agents is limited. We develop a decentralized actor-critic learning f…
Combined Learning and Control: A New Paradigm for Optimal Control with Unknown Dynamics
Panagiotis Kounatidis, Andreas A. Malikopoulos
In this paper, we present the combined learning-and-control (CLC) approach, which is a new way to solve optimal control problems with unknown dynamics by unifying model-based contr…
Real-time autonomous magnetic microrobot navigation across dynamic and biologically relevant environments
Yanda Yang, Max Sokolich, Fatma Ceren Kirmizitas +3
Autonomous microrobots could enable minimally invasive interventions in confined biological environments, but their operation requires real-time navigation among moving obstacles a…
Spatiotemporal Forecasting of Incidents and Congestion with Implications for Sustainable Traffic Control
Tony Kinchen, Ting Bai, Nishanth Venkatesh S. +1
Urban traffic anomalies, such as collisions and disruptions, threaten the safety, efficiency, and sustainability of transportation systems. In this paper, we present a simulation-b…
When Does Selfishness Align with Team Goals? A Structural Analysis of Equilibrium and Optimality
Gehui Xu, Thomas Parisini, Andreas A. Malikopoulos
This paper investigates the relationship between the team-optimal solution and the Nash equilibrium (NE) to assess the impact of self-interested decisions on team performance. In c…
A United Framework for Planning Electric Vehicle Charging Accessibility
Tony Kinchen, Panagiotis Typaldos, Andreas A. Malikopoulos
The shift towards electric vehicles (EVs) is crucial for establishing sustainable and low-emission urban transportation systems. However, the success of this transition depends on…
VisioPath: Vision-Language Enhanced Model Predictive Control for Safe Autonomous Navigation in Mixed Traffic
Shanting Wang, Panagiotis Typaldos, Chenjun Li +1
In this paper, we introduce VisioPath, a novel framework combining vision-language models (VLMs) with model predictive control (MPC) to enable safe autonomous driving in dynamic tr…
Teaching Cars to Drive: Spotlight on Connected and Automated Vehicles
Filippos N. Tzortzoglou, Andreas A. Malikopoulos
In recent decades, society has witnessed significant advancements in emerging mobility systems. These systems refer to transportation solutions that incorporate digital technologie…
On the Robustness of Derivative-free Methods for Linear Quadratic Regulator
Weijian Li, Panagiotis Kounatidis, Zhong-Ping Jiang +1
Policy optimization has drawn increasing attention in reinforcement learning, particularly in the context of derivative-free methods for linear quadratic regulator (LQR) problems w…
Handling Pedestrian Uncertainty in Coordinating Autonomous Vehicles at Signal-Free Intersections
Filippos N. Tzortzoglou, Andreas A. Malikopoulos
In this paper, we provide a theoretical framework for the coordination of connected and automated vehicles (CAVs) at signal-free intersections, accounting for the unexpected presen…
A Coordinated Routing Approach for Enhancing Bus Timeliness and Travel Efficiency in Mixed-Traffic Environment
Tanlu Liang, Ting Bai, Andreas A. Malikopoulos
This paper proposes a coordinated routing approach that investigates the use of connected and automated vehicles (CAVs) in dedicated bus lanes. The aim is to improve bus schedule a…
Platoon Coordination and Leader Selection in Mixed Transportation Systems via Dynamic Programming
Ying Wang, Ting Bai, Andreas A. Malikopoulos
With the growing penetration of electric trucks, freight transportation is transitioning toward a mixed system comprising both fuel-powered and electric trucks. Enhancing truck pla…
AI Recommendation Systems for Lane-Changing Using Adherence-Aware Reinforcement Learning
Weihao Sun, Heeseung Bang, Andreas A. Malikopoulos
In this paper, we present an adherence-aware reinforcement learning (RL) approach aimed at seeking optimal lane-changing recommendations within a semi-autonomous driving environmen…
Safe and Efficient Coexistence of Autonomous Vehicles with Human-Driven Traffic at Signalized Intersections
Filippos N. Tzortzoglou, Logan E. Beaver, Andreas A. Malikopoulos
The proliferation of connected and automated vehicles (CAVs) has positioned mixed traffic environments, which encompass both CAVs and human driven vehicles (HDVs), as critical comp…
Distributed Mixed-Integer Quadratic Programming for Mixed-Traffic Intersection Control
Viet-Anh Le, Andreas A. Malikopoulos
In this paper, we develop a distributed solution framework for coordinating traffic light systems and connected automated vehicles (CAVs) in mixed-traffic intersections. We formula…
Robust Accelerated Dynamics for Subnetwork Bilinear Zero-Sum Games with Distributed Restarting
Weijian Li, Lacra Pavel, Andreas A. Malikopoulos
In this paper, we investigate distributed Nash equilibrium seeking for a class of two-subnetwork zero-sum games characterized by bilinear coupling. We present a distributed primal-…
Route Recommendations for Traffic Management Under Learned Partial Driver Compliance
Heeseung Bang, Jung-Hoon Cho, Cathy Wu +1
In this paper, we aim to mitigate congestion in traffic management systems by guiding travelers along system-optimal (SO) routes. However, we recognize that most theoretical approa…