Provable Transformer Context Compression for In-Context Reinforcement Learning

Yajie Zhao, Yingjun Mo, Zhiyong Wang +3

Transformers can perform in-context reinforcement learning without parameter updates. However, existing theoretical constructions often require context sizes that grow with the num…