Supporting Conversational Case-Based Reasoning in an Integrated Reasoning Framework
D. Aha, L. Breslow, and T. Maney. Case-Based Reasoning Integrations. Papers from the AAAI Workshop, (1998)
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.
%0 Conference Paper
%1 AhaBreslowManey98
%A Aha, David W.
%A Breslow, Leonard A.
%A Maney, Tucker
%B Case-Based Reasoning Integrations. Papers from the AAAI Workshop
%D 1998
%E Aha, David
%E Daniels, Jody J.
%K Planning, Generative Case-Based Machine Reasoning, Model-Based Learning Conversational
%T Supporting Conversational Case-Based Reasoning in an Integrated Reasoning Framework
%X 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.
@inproceedings{AhaBreslowManey98,
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.},
added-at = {2006-11-14T09:19:23.000+0100},
author = {Aha, David W. and Breslow, Leonard A. and Maney, Tucker},
biburl = {https://www.bibsonomy.org/bibtex/2ba6f8048e673ccb477c94fffedad7742/thorob67},
booktitle = {Case-Based Reasoning Integrations. Papers from the {AAAI} Workshop},
editor = {Aha, David and Daniels, Jody J.},
interhash = {cd025ba946fc9cefa5e2014b11f6a210},
intrahash = {ba6f8048e673ccb477c94fffedad7742},
keywords = {Planning, Generative Case-Based Machine Reasoning, Model-Based Learning Conversational},
timestamp = {2006-11-14T09:19:23.000+0100},
title = {Supporting Conversational Case-Based Reasoning in an Integrated Reasoning Framework},
year = 1998
}