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.
Fall
2006
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
Three additional papers
describe other issues. All approaches will be compared, and a framework for
integrating MBR and CBR will be synthesized during the course.
Book
Janet Kolodner:
Case-Based Reasoning. Pages 1- 140.
Papers
1.
B.
Díaz-Agudo, P. González-Calero: An
architecture for knowledge-intensive CBR systems (EWCBR 2000, LNAI Springer 2000)
2.
B.
Díaz-Agudo, P. González-Calero:. A declarative
similarity framework for knowledge-intensive CBR (ICCBR, LNAI Springer 2001)
3.
J.
L. Arcos, E. Plaza: Inference
and reflection in the object-centered representation langauge Noos (FGCS,
1996)
4.
J.L. Arcos, R. Lopez de Mantaras, X. Sierra: SaxeX: a case-based reasoning system for generating expressive musicalperformances. (Int. Comp. Music Conf., ICMC 1997).
5.
E.
Plaza, J. L. Arcos: Constructive
adaptation. (ECCBR 2002, Sprinegr, LNAI, 2002).
6.
D.
Leake: Focusing
construction and selection of abductive hypotheses. (IJCAI 1993. pp 24-29.)
7.
A. Aamodt: Knowledge-intensive
case-based reasoning in Creek. (ECCBR 2004. LNAI 3155, Spinger, 2004. pgs. 1-15.)
8.
A. Aamodt: Modeling
the knowledge contents of CBR systems. (ICCBR 2001, LNAI Springer).
9.
K.
Branting, J. Hastings, J. Lockwood: Integrating
cases and models for prediction in biological systems. (Int. Conf. AI &
Law, 1999).
10.
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.).
Seminar plan
We will have five meetings
to discuss the papers. 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. Each paper is presented by a students, who summarizes it,
points out particular scientific issues of interest, research evaluation method
applied, and strong and weak points of the paper. All students have to read the
papers addressed and prepare for discussions.
The seminar meetings are on
Wednesdays from 14:00 to 15:00.
Students assigned to the
course: Tore Bruland, Ole Edsberg, Jon Espen Ingvaldsen, Frode Sørmo.
Time schedule:
15/09 Start-up.
29/09 Kolodner’s book. Pres. by all 4
students.
03/11 Papers 1 (Jon), 2 (Tore), 3 (Ole), 4 (Frode).
10/11 Summary and continued discussions of papers
1-4. Everyone reads all papers.
17/11 Papers 5 (Ole), 6 (Tore), 7 (Jon), 8
(Frode).
1/12 Papers 9 (Ole, Jon), 10 (Tore, Frode).
15/12 Oral exam.
A good general Web-link for
all types of AI issues is the AAAI-page.
It has a lot of subpages, also related to our theme. Take a look at the
Case-Based Reasoning, and the Ontologies pages, for example.
NTNU-IDI, September 2006
Agnar Aamodt.