Integrating Cognitive Architectures with Foundation Models: Cognitively-Guided Few-Shot Learning to Support Trusted Artificial Intelligence - Thomson, Robert H.; Bastian, Nathaniel D. (Proceedings of the AAAI Symposium Series, 2024)
We present an updated position integrating cognitive architectures into workflow by utilizing the architecture for what it does most effectively: human-like few-shot learning integrating the vast amount of data stored by foundation models. By supplementing the language-generation capabilities with the constraints of cognitive-architectures guiding prompts, it should be possible to generate more relevant output and possibly even predict when the foundation model is hallucinating. Recent advances in few-shot learning capabilities of cognitive architectures in applied domains will be discussed with some parallel capabilities described by foundation models. Just as we use research from social psychology to 'nudge' people into making informed decisions, we should be able to use cognitive architectures to 'nudge' foundation models into developing more human-relevant content.