14 citations · 24 across the 4 of their papers we have counts for
3 papers · 1 filter
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning
Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18
Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a narrow slice of what RL offers.…
Solving Deep Reinforcement Learning Tasks with Evolution Strategies and Linear Policy Networks
Annie Wong, Jacob de Nobel, Thomas Bäck +2
Although deep reinforcement learning methods can learn effective policies for challenging problems such as Atari games and robotics tasks, algorithms are complex, and training time…
Deep Multiagent Reinforcement Learning: Challenges and Directions
Annie Wong, Thomas Bäck, Anna V. Kononova +1
This paper surveys the field of deep multiagent reinforcement learning. The combination of deep neural networks with reinforcement learning has gained increased traction in recent…