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http://bura.brunel.ac.uk/handle/2438/28132
Title: | Computational Argumentation-based Chatbots: a Survey |
Authors: | Castagna, F Kokciyan, N Sassoon, I Parsons, S Sklar, E |
Keywords: | cs.AI |
Issue Date: | 7-Jan-2024 |
Publisher: | Cornell University |
Citation: | Castagna, F. et al. (2024) 'Computational Argumentation-based Chatbots: a Survey', arXiv:2401.03454v1 [cs.AI], pp. 1 - 38. doi: 10.48550/arXiv.2401.03454. |
Abstract: | Chatbots are conversational software applications designed to interact dialectically with users for a plethora of different purposes. Surprisingly, these colloquial agents have only recently been coupled with computational models of arguments (i.e. computational argumentation), whose aim is to formalise, in a machine-readable format, the ordinary exchange of information that characterises human communications. Chatbots may employ argumentation with different degrees and in a variety of manners. The present survey sifts through the literature to review papers concerning this kind of argumentation-based bot, drawing conclusions about the benefits and drawbacks that this approach entails in comparison with standard chatbots, while also envisaging possible future development and integration with the Transformer-based architecture and state-of-the-art Large Language models. |
Description: | The article archived on this institutional repository is a preprint. It has not been certified by peer review. |
URI: | https://bura.brunel.ac.uk/handle/2438/28132 |
Other Identifiers: | ORCID iD: arXiv:2401.03454v1 [cs.AI] |
Appears in Collections: | Dept of Electronic and Electrical Engineering Research Papers |
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Preprint.pdf | Copyright © 2024 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). | 563.57 kB | Adobe PDF | View/Open |
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