Enhancing End-to-End Multi-Task Dialogue Systems: A Study on Intrinsic Motivation Reinforcement Learning Algorithms for Improved Training and Adaptability-Reference-Cited by-同舟云学术

Enhancing End-to-End Multi-Task Dialogue Systems: A Study on Intrinsic Motivation Reinforcement Learning Algorithms for Improved Training and Adaptability

Published:2024-02-05 Issue: Volume:12 Page:335-340
ISSN:
Container-title:2024 IEEE 18th International Conference on Semantic Computing (ICSC)
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Author:

Kamuni Navin¹,Shah Hardik²,Chintala Sathishkumar³,Kunchakuri Naveen⁴,Alla Sujatha⁵

Affiliation:

1. AI ML M.Tech BITS Pilani WILP,USA

2. Rochester Institute of Technology,Department of IT,USA

3. Fisher Investments,Department of IT,USA

4. Eudoxia Resarch University,Department of IT,USA

5. Old Dominion University,Norfolk,Virginia,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10475597/10475598/10475629.pdf?arnumber=10475629

Reference42 articles.

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