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A Socially Acceptable Conversational Agent Based on Cognitive Modeling and Machine Learning

  • Anatoly A. Dolgikh,
  • Alexei V. Samsonovich

摘要

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.