3 papers
cs.LG2026
A Controlled Study of Double DQN and Dueling DQN Under Cross-Environment Transfer
Azkaa Nasir, Fatima Dossa, Muhammad Ahmed Atif +1
Transfer learning in deep reinforcement learning is often motivated by improved stability and reduced training cost, but it can also fail under substantial domain shift. This paper…
cs.MA2026
Does Centralized Learning Help Embodied Agents Coordinate, and When Can a Tabular Study Tell?
Muhammad Ahmed Atif, Nehal Naeem Haji, Mohammad Shahid Shaikh +1
Tabular studies are a common way to compare independent and centralized multi-agent learners, because they avoid function approximation. A natural expectation is that centralized l…
cs.CY2025
Bridging the Gap Between Theoretical and Practical Reinforcement Learning in Undergraduate Education
Muhammad Ahmed Atif, Mohammad Shahid Shaikh
This innovative practice category paper presents an innovative framework for teaching Reinforcement Learning (RL) at the undergraduate level. Recognizing the challenges posed by th…