2 papers
cs.LG2025
Recurrent Off-Policy Deep Reinforcement Learning Doesn't Have to be Slow
Tyler Clark, Christine Evers, Jonathon Hare
Recurrent off-policy deep reinforcement learning models achieve state-of-the-art performance but are often sidelined due to their high computational demands. In response, we introd…
cs.AI2025
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC
Tyler Clark, Mark Towers, Christine Evers +1
Rainbow Deep Q-Network (DQN) demonstrated combining multiple independent enhancements could significantly boost a reinforcement learning (RL) agent's performance. In this paper, we…