Fall
2006
A selected
set of book chapters and papers related to the combination of case-based
reasoning with f model-based reasoning will be discussed. The actual focus will
to some extent depend on the project and interests of the students taking the
course.
This is a doctoral course run as a self-study course with guidance.
We will have four meetings, in addition to the start-up meeting. Each time we will have a set of papers for discussion, to be presented
by the course students. The presentations should focus on the motivation for the research described, the research goal(s), the research method, the results,
and a discussion of the results. Particular emphasis should be on th erepresentation of cases and general domain knowledge, the model-based and case-based reasoning methods,
and the strengths and weaknesses of those approaches.
The students are assumed to work with the topics of the respective papers in between the
meetings, and to browse the Internet or use other sources to fill in missing
details. The students are also encouraged to arrange group meetings between the
scheduled meetings. All students have to read the
papers addressed and prepare for discussions during the course meetings.
Background assumed (from ML+CBR course)
A. Aamodt and E. Plaza, 1994: Case-based reasoning; Foundational issues, methodological variations, and system approaches. AI Communications, 7(1):39–59.
Agnar Aamodt: Explanation-driven case-based reasoning, In S. Wess, K. Althoff, M. Richter (eds.): Topics in Case-based reasoning. Springer Verlag, 1994. pp 274-288.
A. Aamodt: Knowledge-intensive
case-based reasoning in Creek. (ECCBR 2004. LNAI 3155, Spinger, 2004. pgs. 1-16.)
Janet Kolodner's book:
Case-Based Reasoning (1993). Pages 1- 140.
There will be two issues
focused: 1) Modeling and representation 2) Utilizing general models to improve
the CBR reasoning process.
Inparticular, we will focus on research done in three research groups who are
active in this area:
- The group at Universidad Complutense in Madrid, lead by Pedro Gonzáles-Calero
and Belén Díaz-Agudo
- The IIIA group in Barcelona, lead by Enric Plaza
- The Creek work done here at IDI
Papers
*
David Aha: The omniprescence of case-based reasoning in science
and application (Knowledge-Based Systems, Vol. 11 (5-6), 1998. pp. 261-273.)
* Ramon López de Mántaras, David McSherry, Derek Bridge, David Leake, Barry Smyth, Susan Craw, Boi Faltings, Mary Lou Maher, Michael Cox, Kenneth Forbus, Mark Keane, Agnar Aamodt, and Ian Watson: Retrieval, reuse, revision, and retention in case-based reasoning (Knowledge Engineering Review, Vol. 20, Issue 03, September 2005. Cambridge University Press. pp 215-240.)
*
Cindy Marling, Edwina Rissland and Agnar Aamodt: Integrations with case-based reasoning (Knowledge Engineering Review, Vol. 20, Issue 03, September 2005. Cambridge University Press. pp 241-245.)
*
A. Aamodt, Mads Nygård:
Differentroles and mutual dependencies of data, information, and knowledge - an AI perspective on their integration, .
Data and Knowledge Enigneering 16 (1995), pp 191-222.
*
Paal Skalle, Jostein Sveen, Agnar Aamodt:
Improved efficiency of oil well drilling through case-based reasoning.,Proceedingsof PRICAI 2000, The Sixth Pacific Rim International
Conference on Artificial Intellignece, Melbourne August-September 2000. LectureNotes in Artificial Intelligence,
Springer Verlag, 2000. pp 713-723.
*
Pål Skalle, Agnar Aamodt:
Knowledge-based decision support in oil well drilling.,Zhongzhi Shi (ed.), Proceedings of the ICIIP 2004,
International Conference on Intelligent Information Systems. Beijing, China, October 21 - 23, 2004. pp443-456.
*
Morten Grimnes, Agnar Aamodt:
A two-layer case-based reasoning architecture
for medical image understanding.,In Smith, I., Faltings, B. (eds).
Advances in case-based reasoning, (Proc. EWCBR-96), Springer Verlag, Lecture Notes in ArtificialIntelligence 1168,
1996. pp 164-178.
* N. Fridman and C.D. Hafner: The
state of the art in ontology design. (AI
Magazine, Fall
1997, pp. 53-74)
*
B.
Díaz-Agudo, P. González-Calero: An
architecture for knowledge-intensive CBR systems (EWCBR 2000, LNAI Springer 2000). pp 37-48.
*
B.
Díaz-Agudo, P. González-Calero:. A declarative
similarity framework for knowledge-intensive CBR (ICCBR, LNAI Springer 2001. pp 158-172.
*
J.
L. Arcos, E. Plaza: Inference
and reflection in the object-centered representation langauge Noos Future Generation Computer Systems
Volume 12 , Issue 2-3 (September 1996). pp. 173-188.
*
J.L. Arcos, R. Lopez de Mantaras, X. Sierra: SaxeX: a case-based reasoning system for generating expressive musicalperformances.
Proceedings of the International Computer Music Conference, 1997.
pages 329-336.
*
S.
Brüningshouse, K. Ashley: Combining case-based and model-based
reasoning for predicting teh outcome of legal cases. (Case-based reasoning research and development, ICCBR 2003. LNAI
2689. pp. 246-260.).
NTNU-IDI, September 2006
Agnar Aamodt.