arXiv · 2109.09597
Two Approaches to Building Collaborative, Task-Oriented Dialog Agents through Self-Play
Abstract
Task-oriented dialog systems are often trained on human/human dialogs, such as collected from Wizard-of-Oz interfaces. However, human/human corpora are frequently too small for supervised training to be effective. This paper investigates two approaches to training agent-bots and user-bots through self-play, in which they autonomously explore an API environment, discovering communication strategies that enable them to solve the task. We give empirical results for both reinforcement learning and game-theoretic equilibrium finding.
Explore related subjects
Keep this discovery
Arkady Arkhangorodsky, Scot Fang, Victoria Knight, Ajay Nagesh, Maria Ryskina, Kevin Knight. 2021-09-20. Two Approaches to Building Collaborative, Task-Oriented Dialog Agents through Self-Play. https://arxiv.org/abs/2109.09597
Cite the original work for its findings. Save a collection to share your selection of sources.