Reasoning and Learning with Imperfect Casebases: An Agent Perspective with An Expert Model

Authors

Leen-Kiat Soh, University of NebraskaFollow

Date of this Version

2004

Comments

University of Nebraska-Lincoln, Computer Science and Engineering
Technical Report # TR-UNL-CSE-2004-0002

Abstract

Traditionally, case-based reasoning (CBR) (e.g., Watson and Marir 1994) assumes that the cases in the casebase are correct, useful in both time and space. Otherwise, the cases would not have been stored in the casebase in the first place. Cases are supposed to be useful in guiding us to a successful solution, or in preventing us from repeating the same failure.