A Case-based Reasoning (CBR) system uses lazy "generalization" from
past similar cases to the present task. Past similar cases are
retrieved through similarity estimates between the current problem 
and the precedent cases
that the system has
access to.
The
crucial assumption in a CBR system is that the more similar the
current problem is to
a
precedent 
, the more
similar
the solution of is to
the
solution of 
. In
recent times,
CBR techniques have enjoyed an immense popularity among researchers
and practitioners of AI, building intelligent tools for a number of
applications[Aamodt &Plaza1994].
Techniques for distributed case-based
reasoning are being developed with the aim of leveraging the insights
gained from building and using such applications but at the same time
coping with the distributed nature of the knowledge available in many
applications. Viewing Corporate Memories as Distributed Case Libraries
(or Distributed Case Bases) provides us with ways to exploit these
techniques to develop semantically rich and flexible tools for
knowledge management in distributed environments.