21 citations · 118 across the 15 of their papers we have counts for
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cs.LG2024★ 17 cited
Continual Deep Reinforcement Learning with Task-Agnostic Policy Distillation
Muhammad Burhan Hafez, Kerim Erekmen
Central to the development of universal learning systems is the ability to solve multiple tasks without retraining from scratch when new data arrives. This is crucial because each…
cs.LG2024★ 1 cited
QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning
Mostafa Kotb, Cornelius Weber, Muhammad Burhan Hafez +1
Inspired by the success of the Transformer architecture in natural language processing and computer vision, we investigate the use of Transformers in Reinforcement Learning (RL), s…