  This article describes a novel approach to expand in run-time the knowledge
base of an Artificial Conversational Agent. A technique for automatic knowledge
extraction from the user's sentence and four methods to insert the new acquired
concepts in the knowledge base have been developed and integrated into a system
that has already been tested for knowledge-based conversation between a social
humanoid robot and residents of care homes. The run-time addition of new
knowledge allows overcoming some limitations that affect most robots and
chatbots: the incapability of engaging the user for a long time due to the
restricted number of conversation topics. The insertion in the knowledge base
of new concepts recognized in the user's sentence is expected to result in a
wider range of topics that can be covered during an interaction, making the
conversation less repetitive. Two experiments are presented to assess the
performance of the knowledge extraction technique, and the efficiency of the
developed insertion methods when adding several concepts in the Ontology.
