Abstract
Large Language Models (LLM) enable recognition of the topic of arbitrary statements, as well as their emotional coloring, but do not “understand” the logic of emotions, despite the fact that they can often generate adequate responses in a given context. On the other hand, cognitive architectures such as eBICA are able to model the dynamics of emotional states in the general case but require assistance in understanding the meaning of statements and generating responses to them. This work introduces a new way to integrate LLM and eBICA, allowing them to complement each other. An experimental study based on the paradigms “virtual receptionist” and “virtual psychologist” is presented, showing encouraging results.
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Acknowledgments
The authors consider it their pleasant duty to thank those who contributed to the work on this project: NRNU MEPhI Faculty Member Daria V. Tikhomirova, NRNU MEPhI Graduate Students Alena Anisimova, Aleksei Mikhnev, and Vladimir Tsarkov.
The work was supported by the Russian Science Foundation Grant No. 22-11-00213, https://rscf.ru/project/22-11-00213/.
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Dolgikh, A.A., Samsonovich, A.V. (2024). A Socially Acceptable Conversational Agent Based on Cognitive Modeling and Machine Learning. In: Samsonovich, A.V., Liu, T. (eds) Biologically Inspired Cognitive Architectures 2023. BICA 2023. Studies in Computational Intelligence, vol 1130. Springer, Cham. https://doi.org/10.1007/978-3-031-50381-8_31
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