On the Limitations of Memory Based Reasoning
File Type:
PDFItem Type:
Technical ReportDate:
1994-11Citation:
Cunningham, Padraig; Smyth, Barry; Veale, Tony. 'On the Limitations of Memory Based Reasoning'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-94-12, 1994, pp7Download Item:
Abstract:
Memory-Based Reasoning (MBR) represents a radical new departure in AI research. Whereas work in
symbolic AI is based on inference and knowledge representation MBR depends on using a large
memory of examples as a reasoning base. The MBR methodology is empirical so a typical system
does not contain an explicit domain model. This means that MBR systems are quick to set up so the
methodology shows considerable promise for knowledge based systems development. Indeed some
impressive full scale systems have been demonstrated. In this paper we argue that despite this initial
success there are considerable limitations to what can be achieved with MBR. We believe that the
absence of a domain model means that MBR will not succeed in complex applications. We illustrate
problems in natural language processing and planning that will require access to domain theories in
their solution. Our conclusion is that the memory oriented philosophy of MBR has advantages but, for
truly intelligent systems, this philosophy is better realised in the CBR paradigm where it can be
integrated with a strong domain theory.
Description:
Also in Proceedings of the Second European Workshop on Case-Based Reasoning, Chantilly, France.Publisher:
Trinity College Dublin, Department of Computer ScienceType of material:
Technical ReportCollections
Series/Report no:
Computer Science Technical ReportTCD-CS-94-12
Availability:
Full text availableKeywords:
Computer ScienceMetadata
Show full item recordLicences: