Towards Learning Through Open-Domain Dialog [article]

Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos
2022 arXiv   pre-print
The development of artificial agents able to learn through dialog without domain restrictions has the potential to allow machines to learn how to perform tasks in a similar manner to humans and change how we relate to them. However, research in this area is practically nonexistent. In this paper, we identify the modifications required for a dialog system to be able to learn from the dialog and propose generic approaches that can be used to implement those modifications. More specifically, we
more » ... cuss how knowledge can be extracted from the dialog, used to update the agent's semantic network, and grounded in action and observation. This way, we hope to raise awareness for this subject, so that it can become a focus of research in the future.
arXiv:2202.03040v1 fatcat:723ekej7hfgzrbasdwvjyoifbu