Itsugun_cho Deep Rl With Hierarchical Action Exploration for Dialogue Generation 2023
[TOC] Title: Deep RL With Hierarchical Action Exploration for Dialogue Generation Author: Itsugun Cho et. al. Publish Year: 22 Mar 2023 Review Date: Thu, Mar 30, 2023 url: https://arxiv.org/pdf/2303.13465v1.pdf Summary of paper Motivation Approximate dynamic programming applied to dialogue generation involves policy improvement with action sampling. However, such a practice is inefficient for reinforcement learning because the eligible (high action value) responses are very sparse, and the greedy policy sustained by the random sampling is flabby....