38 citations · 97 across the 57 of their papers we have counts for
66 papers
A Collision-Aware Predictive Rerouting Framework for Connected and Automated Vehicles
Tony Kinchen, Ting Bai, Andreas A. Malikopoulos
In this paper, we investigate the problem of mitigating non-recurrent congestion in urban transportation networks through predictive and adaptive routing for connected and automate…
TempoKV: Predictive KV Cache Quantization for Autoregressive Video Generation
Jiahui Hu, Weile Mo, Peiliang Cai +5
Autoregressive (AR) video diffusion models enable streaming generation of long videos but suffer from significant memory overhead due to the rapidly growing KV cache. Existing KV c…
Policy Improvement From Private Information For Decentralized LQG Teams
Hung T. Nguyen, Andreas A. Malikopoulos
Sharing of information in multiagent systems allow for improved coordination. Delays in communication can cause asymmetries in information, causing classical results to fail. We st…
COOL: Curiosity-Driven Object Ownership Learning for Personalized Robotic Assistance
Samira Huber, Ruben Hammele, Sören Pirk
Robots are increasingly expected to provide personalized services in everyday environments. To do so, they must ground natural-language commands such as "Where is my backpack?" or…
Preference-Adaptive Control in Autonomous Driving
Zhongyu Mo, Shanting Wang, Huaijin Hu +1
In this paper, we present a preference-adaptive receding-horizon control framework for autonomous driving that accounts for passenger preferences and motion-sickness susceptibility…
Closed-Loop Refinement and Execution for Learned Driving Planners
Huaijin Hu, Shanting Wang, Zhongyu Mo +1
Learning-based driving planners are usually trained and evaluated in open loop against logged trajectories. In closed loop, a trajectory with small displacement error can still sta…
Hierarchical Multi-agent Reinforcement Learning for Warehouse Robot Coordination under Communication Loss
Weihao Sun, Gehui Xu, Andreas A. Malikopoulos
In this paper, we propose a hierarchical multi-agent reinforcement learning framework for coordinating robot teams in warehouse environments under communication loss. We partition…
A Decentralized Partially Observable Team Decision Methodology with Delayed Information Sharing
Xiaoxing Ren, Thomas Parisini, Andreas A. Malikopoulos
We study decentralized partially observable team decision problems with low-rank latent dynamics and unknown system models. The proposed framework combines team-theoretic equivalen…
Cross-fitted Proximal Learning for Model-Based Reinforcement Learning
Nishanth Venkatesh, Andreas A. Malikopoulos
Model-based reinforcement learning is attractive for sequential decision-making because it explicitly estimates reward and transition models and then supports planning through simu…
Adaptive Mitigation of Insider Threats via Off-Policy Learning
Gehui Xu, Kaiwen Chen, Zhong-Ping Jiang +2
An insider is a team member who covertly deviates from the team's optimal collaborative strategy to pursue a private objective while still appearing cooperative. Such an insider ma…
When an Approximate Model Suffices for Optimal Control
Andreas A. Malikopoulos
In this paper, we develop an optimal control framework for dynamical systems when only an approximate model of the underlying plant is available. We consider a setting in which the…
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…