4 papers
Toward Quantum-Aware Machine Learning: Improved Prediction of Quantum Dissipative Dynamics via Complex Valued Neural Networks
Muhammad Atif, Arif Ullah, Ming Yang
Accurately modeling quantum dissipative dynamics remains challenging due to environmental complexity and non-Markovian memory effects. Although machine learning provides a promisin…
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…
Embodiment-Induced Coordination Regimes in Tabular Multi-Agent Q-Learning
Muhammad Ahmed Atif, Nehal Naeem Haji, Mohammad Shahid Shaikh +1
Centralized value learning underlies a broad class of multi-agent reinforcement learning methods, but its claimed advantage is typically evaluated in settings that confound coordin…
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…