Experimental Study of a Similarity Metric for
Retrieving Pieces from Structured Plan Cases:
Its Role in the Originality of Plan Case Solutions

Lus Macedo (1,2), Francisco C. Pereira (2), Carlos Grilo (2), Amlcar Cardoso (2)

(1) Instituto Superior de Engenharia de Coimbra, 3030 Coimbra, Portugal
(macedo@dei.uc.pt)
(2) CISUC - Centro de Informtica e Sistemas da Universidade de Coimbra, Polo II,
3030 Coimbra, Portugal
(francisco@alma.uc.pt, grilo@alma.uc.pt, amilcar@dei.uc.pt)

Abstract. This paper describes a quantitative similarity metric and its
contribution to achieve original plan solutions. This similarity metric is used
by an iterative process of piece retrieval from structured plan cases. Within
our approach plan cases are tree-like networks of pieces (goals and actions).
These case pieces are ill-related each other by links (explanations). These
links may be classified as hierarchical or temporal, antecedent or consequent,
and explicit or implicit. Besides links, each case piece has also information
about its properties (the attributes-value pairs), its hierarchical and temporal
position in the case (the address), and about its constraints in the relationship
with others (the constraints). The similarity metric computes a similarity
value between two case pieces taking into account similarities between these
case pieces information types. Each time a problem is proposed, different
weights are given to some of those similarities, with the aim of solving it
with an original solution. This similarity metric is used by the system
INSPIRER (ImagiNation taking as Source Past and Imperfectly REalated
Reasonings). We illustrate the role of the similarity metric in the creativity of
solutions, focusing specially their originality, with the presentation of the
experimental results obtained in the musical composition domain, which is
considered by us as a planning domain.

References
Balaban, M., (1992). Musical Structures: Interleaving the Temporal and Hierarchical Aspects
in Music. In Understanding Music with IA: Perspectives in Music Cognition, MIT Press.
Barletta, R., Mark, W., (1988). Breaking cases into pieces, in Proceedings of a Case-Based
Reasoning Workshop, St. Paul, MN.
Barletta, R., Mark, W., (1989). Explanation-Based Indexing of Cases, in Proceedings of a
Case-Based Reasoning Workshop, Morgan-Kaufmann.
Bento, C. and Costa, E., (1994). A Similarity Metric for Retrieval of Cases Imperfectly
Explained, in First European Workshop on Case-Based Reasoning, Kaiserslautern.
Bento, C., Macedo, L. and Costa, E., (1994). RECIDE - Reasoning with Cases Imperfectly
Described and Explained, in Second European Workshop on Case-Based Reasoning..
Duda, R., and Hart, P., (1973). Pattern Classification and Scene Analysis, New York: Wiley.
Hammond, K., (1986). Case Based Planning: An Integrated Theory of Planning, Learning
and Memory, PhD Dissertation, Yale University.
Kolodner, J., and Riesbeck, C., (1986). Experience, Memory, and Reasoning, Lawrence
Erlbaum Associates, Hillsdale, NJ.
Kolodner, J., (1988). Retrieving events from a Case Memory: a parallel implementation, in
Proceedings of a Case-Based Reasoning Workshop, San Mateo, CA, Morgan-Kaufmann.
Kolodner, J., (1989). Judging Which is the Best Case for a Case-Based Reasoner, in Case-Based 
Reasoning: Proceedings of a Workshop, florida, Morgan-Kaufmann.
Koton, P., (1989). Using Experience in Learning and Problem Solving, Massachusets
Institute of Technology, Laboratory of Computer Science (Ph D diss.), MIT/LCS/TR-
441.
Macedo, L., Pereira, F., Grilo, C. and Cardoso, M., (1996a). Plan Cases as Strnctured
Networks of Hierarchical and Temporal Related Case Pieces, Third European Workshop
on Case-Based Reasoning, Lausanne.
Macedo, L., Pereira, F., Grilo, C. and Cardoso, M., (1996b). Solving Planning Problems that
Require Creative Solutions using a Hierarchical Case-Based Planning Approach,
International Conference on Knowledge Based Computer Systems, India.
Macedo, L., Pereira, F., Grilo, C. and Cardoso, M., (1996c). A Case-Based Computational
Model for Creative Planning, Proceedings of the First European Workshop on Cognitive
Modeling, Berlim.
Macedo, L., Pereira, F., Grilo, C. and Cardoso, M., (1997a). A Computational Model for the
Creative Planning Faculties of Mind, in Mind Modelling - A Cognitive Science
Approach to Reasoning, Learning and Discover, Schmith, U., Krems, J.F., and Wysotzki,
F., (Editors).(forthcomming)
Plaza, E., (1995). Cases as terms: A feature term approach to the structured representation of
cases, in Proceedings of the First International Conference on Case-Based Reasoning,
Sesimbra, Portugal.
Redmond, M., (1990). Distributed Cases for Case-Based Reasoning; Facilitating Use of
Multiple Cases, In Proceedings of AAAI.
Sycara, K., Navinchandra, D., (1991). Influences: A Thematic Abstraction for Creative Use
of Multiple Cases, in Proceedings of a Case-Based Reasoning Workshop.
Veloso, M., (1992). Learning by Analogical Reasoning in General Problem Solving, Ph D
thesis, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA.
