← Search

Jiuqi Wang

2 accepted papers

2025

Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning

ICLR 2025poster

Traditionally, reinforcement learning (RL) agents learn to solve new tasks by updating their neural network parameters through interactions with the task environment. However, recent works demonstrate that some RL agents, after certain pretraining procedures, can learn to solve unseen new tasks with…

Cited by 8SourcePDFScholar