Noticeably New: Case Reuse in Originality-Driven Tasks

Authors:
Belén Díaz-Agudo;Enric Plaza;Juan A. Recio-García;Josep-Lluís Arcos
Affiliations:
Department of Software Engineering and Artificial Intelligence, Universidad Complutense de Madrid, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Spain;Department of Software Engineering and Artificial Intelligence, Universidad Complutense de Madrid, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Spain
Venue:
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Year:
2008

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Abstract

"Similar problems have similar solutions" is a basic tenet of case-based inference. However this is not satisfied for CBR systems where the task is to achieve originalsolutions -- i.e. solutions that, even for "old problems," are required to be noticeably different from previously known solutions. This paper analyzes the role of reuse in CBR systems in originality driven tasks(ODT), where a new solution has not only to be correct but noticeably different from the ones known in the case base. We perform an empirical study of transformational and generative reuse applied to an originality driven task, namely tale generation, and we analyze how search in the solution space and consistency maintenance are pivotal for ODT during the reuse process.