Ryota Takahashi

Deep RL with Hierarchical Action Exploration for Dialogue Generation

2023 · arXiv (Cornell University)

Traditionally, approximate dynamic programming is employed in dialogue generation with greedy policy improvement through action sampling, as the natural language action space is vast. However, this practice is inefficient for reinforcement learning (RL) due to …