Abstract
Conversational case-based reasoning (CCBR) has been
successfully use to assist in case retrieval tasks. However,
behavioural limitations of CCBR motivate the search for
integrations with other reasoning approaches. This paper briefly
describes our group's ongoing efforts towards enhancing the
inferencing behaviours of a conversational case-based reasoning
development tool named NaCoDAE. In particular, we focus on
integrating NaCoDAE with machine learning, model-based reasoning,
and generative planning modules. This paper defines CCBR, briefly
summarizes the integrations, and explains how they enhance the
overall system.
Users
Please
log in to take part in the discussion (add own reviews or comments).