An Introduction to Case-Based Reasoning*
Case-based reasoning means using old experiences to understand and solve new problems In case-based reasoning, a reasoner remembers a previous situation similar to the current one and uses that to solve the new problem Case- based reasoning can mean adapting old solutions to meet new demands; using old
PRINCIPLES OF CASE-BASED REASONING
The general case-based reasoning paradigm The quality of the new case(s) extracted by the CBR-agent depends upon some of the following criteria: a) The usefulness of the case(s) extracted and selected; b) The ease of use this (these) case(s); c) The validity of the reasoning process; and d) The improvement of knowledge through experience
Problem Solving by Case-Based Reasoning
Dr Thomas Gabel --- Problem Solving by Case-Based Reasoning ---11 05 2010 Advantages of CBR (II) • High Quality of Solutions for Poorly Understood Domains – case-based systems can be made to retain only ``good‘‘ experience in memory – if only little adaptation is necessary for reuse, this will not impair the solution‘s quality too much
Introduction to Machine Learning Case-Based Reasoning
Instance-based learning also includes case-based reasoning methods that use more complex, symbolic representations for instances An overview of the topic can be found in [8] A survey of methods for locally weighted regression is given in [3] Chapter 2 of this syllabus provides a detailed discussion on case-based reasoning
Decision-Theoretic Case-Based Reasoning
experience Case-based reasoning (CBR) is a method for problem solving that uses a database of previously encountered problem solving incidents as its core representation The presumption in CBR is that past problem solving behavior is the best predictor of future problems and solutions
Case-based Reasoning in Health Care
Case-based Reasoning Decision Support System Parameters are set by the clinician based on experience and feedback from the persons and stored in the person’s case This is a “New Calibration Case” new case can be used in a variety of situations, e g to assess the effect of treatment and recovery or to identify dangerous stress levels
An Approach to Legal Ontologies: the Case-Based Reasoning
supporting case-based legal reasoning • Extended example of case-based legal reasoning to be supported by ontology • Distill requirements of a CBR ontology for each role: 1 Support case-based comparisons 2 Distinguish deep and shallow analogies 3 Induce/test hypotheses • Discuss extent requirements met and remaining challenges
CBR chapter 1-3
Soft Computing: Case-Based Reasoning How Does CBR Work? plus some bad loans net monthly income m o n t h l y l o a n r e p a y m e n t 27 Soft Computing: Case-Based Reasonin g Lazy Learning past cases (loans) may tend to form clusters, but you don’t need to find them net monthly income m o n t h l y l o a n r e p a y m e n t g od l ans b ad
Foundations of Artificial Intelligence
• Case indexing • Assign indices to cases to facilitate their retrieval • Features and dimensions tend to be predictive • The system has to retrieve the right case at the right time • Predictive, useful, abstract and concrete Case Based Reasoning - Abstract enough to allow for widening the future use of the case-base;
[PDF] case based reasoning algorithm
[PDF] molecule de l'air
[PDF] molécule d'air formule
[PDF] l'air un mélange de molécules 4ème
[PDF] pourquoi les molécules principales de l'air sont-elles appelées diazote et dioxygène
[PDF] molécule d'air définition
[PDF] diazote et dioxygene dans l'air
[PDF] raisonnement philosophique
[PDF] exemple de raisonnement
[PDF] le raisonnement inductif
[PDF] raisonnement hypothético-déductif exemple
[PDF] raisonnement par contre exemple exercices
[PDF] exercice raisonnement direct
[PDF] contre exemple math