Case-Based Reasoning in Mixed Paradigm Settings and with Learning

Abstract

In this project we investigated: (1) CBR in mixed paradigm settings, in particular in a blackboard-based system, called FRANK, that generated various types of explanations and arguments where supporting tasks, such as case-and rule-based reasoning, were dynamically configured to reflect the user's intended purposes for the report: (2) pure CBR, particularly issues concerning the use of multiple indices and types of case representations, in a system called BankXX. that used classic heuristic best-first search to retrieve information needed for case-based argument: and (3) the application of machine learning techniques to core issues in CBR, such as the problems of learning indices and prototype cased and estimating concept theory drift.

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Document Details

Document Type
Technical Report
Publication Date
Apr 30, 1994
Accession Number
ADA279897

Entities

People

  • Edwina L. Rissland

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence
  • Cognitive Science
  • Computer Science
  • Databases
  • Genetic Algorithms
  • Information Retrieval
  • Information Science
  • Learning
  • Lisp Programming Language
  • Machine Learning
  • Models
  • Prototypes
  • Reasoning
  • Standards
  • Statistical Analysis

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms