4 papers · 1 filter
Methodical Advice Collection and Reuse in Deep Reinforcement Learning
Sahir, Ercüment İlhan, Srijita Das +1
Reinforcement learning (RL) has shown great success in solving many challenging tasks via use of deep neural networks. Although using deep learning for RL brings immense representa…
Action Advising with Advice Imitation in Deep Reinforcement Learning
Ercument Ilhan, Jeremy Gow, Diego Perez-Liebana
Action advising is a peer-to-peer knowledge exchange technique built on the teacher-student paradigm to alleviate the sample inefficiency problem in deep reinforcement learning. Re…
Learning on a Budget via Teacher Imitation
Ercument Ilhan, Jeremy Gow, Diego Perez-Liebana
Deep Reinforcement Learning (RL) techniques can benefit greatly from leveraging prior experience, which can be either self-generated or acquired from other entities. Action advisin…
Student-Initiated Action Advising via Advice Novelty
Ercument Ilhan, Jeremy Gow, Diego Perez-Liebana
Action advising is a budget-constrained knowledge exchange mechanism between teacher-student peers that can help tackle exploration and sample inefficiency problems in deep reinfor…