Authors: Isabella Graßl
Dialogue systems are computer systems which com- municate with humans using natural language. The goal is not just to imitate human communication but to learn from these interactions and improve the system’s behaviour over time. Therefore, different machine learning approaches can be implemented with Reinforcement Learning being one of the most promising techniques to generate a contextually and semantically appropriate response. This paper outlines the current state-of- the-art methods and algorithms for integration of Reinforcement Learning techniques into dialogue systems.
Comments: 6 Pages.
[v1] 2019-03-09 01:41:05
Unique-IP document downloads: 0 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.