Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
11-2024
Abstract
We investigate non-collaborative dialogue agents, which are expected to engage in strategic conversations with diverse users, for securing a mutual agreement that leans favorably towards the system’s objectives. This poses two main challenges for existing dialogue agents: 1) The inability to integrate user-specific characteristics into the strategic planning, and 2) The difficulty of training strategic planners that can be generalized to diverse users. To address these challenges, we propose TRIP to enhance the capability in tailored strategic planning, incorporating a user-aware strategic planning module and a population-based training paradigm. Through experiments on benchmark non-collaborative dialogue tasks, we demonstrate the effectiveness of TRIP in catering to diverse users.
Keywords
Dialogue agents, Non-collaborative dialogues
Discipline
Artificial Intelligence and Robotics | Computer Sciences
Areas of Excellence
Digital transformation
Publication
Proceedings of the Conference on Empirical Methods in Natural Language Processing 19th EMNLP 2024 : Miami, Florida, USA, November 12-16
First Page
424
Last Page
444
Identifier
10.48550/arXiv.2403.06769
Publisher
Association for Computational Linguistics
City or Country
USA
Citation
ZHANG, Tong; HUANG, Chen; DENG, Yang; LIANG, Hongru; LIU, Jia; WEN, Zujie; LEI, Wenqiang; and CHUA, Tat-Seng.
Strength lies in differences! improving strategy planning for non-collaborative dialogues via diversified user simulation. (2024). Proceedings of the Conference on Empirical Methods in Natural Language Processing 19th EMNLP 2024 : Miami, Florida, USA, November 12-16. 424-444.
Available at: https://ink.library.smu.edu.sg/sis_research/9538
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.48550/arXiv.2403.06769