38 citations · 97 across the 57 of their papers we have counts for
11 papers · 1 filter
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…