activity
20232026
most citedSafety Guaranteed Robust Multi-Agent Reinforcement Learning with Hierarchical Control for Connected and Automated Vehicles

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.AI2026

SpecMAGIC: Specification-Guided Multi-Task Generalization in Multi-Agent Reinforcement Learning

Zijian Guo, İlker Işık, H. M. Sabbir Ahmad +1

Multi-task generalization is an important yet underexplored problem in multi-agent reinforcement learning (MARL). Many real-world applications require multi-agent systems to genera…

cs.CV2026

VLM-UQBench: A Benchmark for Modality-Specific and Cross-Modality Uncertainties in Vision Language Models

Chenyu Wang, Tianle Chen, H. M. Sabbir Ahmad +2

Uncertainty quantification (UQ) is vital for ensuring that vision-language models (VLMs) behave safely and reliably. A central challenge is to localize uncertainty to its source, d…

cs.LG2025

Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems

H. M. Sabbir Ahmad, Ehsan Sabouni, Alexander Wasilkoff +6

We address the problem of safe policy learning in multi-agent safety-critical autonomous systems. In such systems, it is necessary for each agent to meet the safety requirements at…

cs.AI2025

One Subgoal at a Time: Zero-Shot Generalization to Arbitrary Linear Temporal Logic Requirements in Multi-Task Reinforcement Learning

Zijian Guo, İlker Işık, H. M. Sabbir Ahmad +1

Generalizing to complex and temporally extended task objectives and safety constraints remains a critical challenge in reinforcement learning (RL). Linear temporal logic (LTL) offe…

eess.SY2024

Reinforcement Learning-based Receding Horizon Control using Adaptive Control Barrier Functions for Safety-Critical Systems

Ehsan Sabouni, H. M. Sabbir Ahmad, Vittorio Giammarino +3

Optimal control methods provide solutions to safety-critical problems but easily become intractable. Control Barrier Functions (CBFs) have emerged as a popular technique that facil…

cs.RO2023★ 1 cited

Safety Guaranteed Robust Multi-Agent Reinforcement Learning with Hierarchical Control for Connected and Automated Vehicles

Zhili Zhang, H M Sabbir Ahmad, Ehsan Sabouni +4

We address the problem of coordination and control of Connected and Automated Vehicles (CAVs) in the presence of imperfect observations in mixed traffic environment. A commonly use…