6 papers
Formal Verification of Learned Multi-Agent Communication Policies via Decision Tree Distillation
Ahmad Farooq, Kamran Iqbal
Multi-agent reinforcement learning (MARL) enables agents to develop coordination strategies through emergent communication, but neural policies lack the formal safety guarantees re…
Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantization
Ahmad Farooq, Kamran Iqbal
Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significantly impact coordination effectiveness.…
Reimagining Peer Review Process Through Multi-Agent Mechanism Design
Ahmad Farooq, Kamran Iqbal
The software engineering research community faces a systemic crisis: peer review is failing under growing submissions, misaligned incentives, and reviewer fatigue. Community survey…
Towards Transparent Ethical AI: A Roadmap for Trustworthy Robotic Systems
Ahmad Farooq, Kamran Iqbal
As artificial intelligence (AI) and robotics increasingly permeate society, ensuring the ethical behavior of these systems has become paramount. This paper contends that transparen…
Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction
Ahmad Farooq, Kamran Iqbal
This paper presents a novel approach that integrates vision foundation models with reinforcement learning to enhance object interaction capabilities in simulated environments. By c…
A Survey of Reinforcement Learning for Optimization in Automation
Ahmad Farooq, Kamran Iqbal
Reinforcement Learning (RL) has become a critical tool for optimization challenges within automation, leading to significant advancements in several areas. This review article exam…