Paper Info
Title
Explanation for Case-Based Reasoning via Abstract Argumentation.
Abstract
Case-based reasoning (CBR) is extensively used in AI in support of several applications, to assess a new situation (or case) by recollecting past situations (or cases) and employing the ones most similar to the new situation to give the assessment. In this paper we study properties of a recently proposed method for CBR, based on instantiated Abstract Argumentation and referred to as AA-CBR, for problems where cases are represented by abstract factors and (positive or negative) outcomes, and an outcome for a new case, represented by abstract factors, needs to be established. In addition, we study properties of explanations in AA-CBR and define a new notion of lean explanations that utilize solely relevant cases. Both forms of explanations can be seen as dialogical processes between a proponent and an opponent, with the burden of proof falling on the proponent.
Year
DOI
Venue
2016
10.3233/978-1-61499-686-6-243
Frontiers in Artificial Intelligence and Applications
Keywords
Field
DocType
Case-Based Reasoning,Abstract Argumentation,Explanation
Automated reasoning,Computer science,Argumentation theory,Abductive reasoning,Artificial intelligence,Case-based reasoning
Conference
Volume
ISSN
Citations 
287
0922-6389
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Kristijonas Cyras1198.81
ken23614.64
Francesca Toni334327.02