  We report on the design and development of the CASPR system, a socialbot
designed to compete in the Amazon Alexa Socialbot Challenge 4. CASPR's
distinguishing characteristic is that it will use automated commonsense
reasoning to truly "understand" dialogs, allowing it to converse like a human.
Three main requirements of a socialbot are that it should be able to
"understand" users' utterances, possess a strategy for holding a conversation,
and be able to learn new knowledge. We developed techniques such as
conversational knowledge template (CKT) to approximate commonsense reasoning
needed to hold a conversation on specific topics. We present the philosophy
behind CASPR's design as well as details of its implementation. We also report
on CASPR's performance as well as discuss lessons learned.
