6 citations · 12 across the 9 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
physics.plasm-ph2023★ 6 cited
Towards practical reinforcement learning for tokamak magnetic control
Brendan D. Tracey, Andrea Michi, Yuri Chervonyi +15
Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbac…
cs.PF2023★ 1 cited
Optimizing Memory Mapping Using Deep Reinforcement Learning
Pengming Wang, Mikita Sazanovich, Berkin Ilbeyi +16
Resource scheduling and allocation is a critical component of many high impact systems ranging from congestion control to cloud computing. Finding more optimal solutions to these p…