Common Sense Reasoning in Diagnostic Systems - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 99

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Common Sense Reasoning in
Diagnostic Systems
Alexander P. Eremeev and Vadim N. Vagin
Moscow Power Engineering Institute (Technical University)
Russia
1. Introduction
The problem of human reasoning modeling (so called “common sense” reasoning) in
artificial intelligence systems and especially in intelligent decision support systems (IDSS) is
very actual nowadays [Vagin et al., 2001]. That is why special attention is turned to case-
based and analogous reasoning methods and models. The analogies and precedents (cases)
can be used in various applications of artificial intelligence (AI) and for solving various
problems, e.g., for diagnostics and forecasting or for machine learning. AI experts model
case-based reasoning by computers in order to develop more flexible models of search for
solutions and learning.
Investigation of mechanisms that are involved in the analogous reasoning process is an
important problem for the specialists in AI. The analogy can be used in various
applications of AI and for solving various problems, e.g., for generation of hypotheses
about an unknown problem domain or for generalizing experience in the form of an
abstract scheme. The great interest in this problem is caused by the necessity of modeling
human reasoning (common sense reasoning) in AI systems and, in particular, in IDSS of
real time.
Reasoning by analogy is to transfer of knowledge obtained from an object to a less studied one
which is similar to the former with respect to some essential properties or attributes.
Reasoning of this kind is a source of scientific hypotheses. Thus, analogy-based reasoning
can be defined as a method that allows to understand a situation when compared with
another one. In other words, an analogy is an inference method that allows to detect likeness
between several given objects due to transfer of facts and knowledge valid for both objects,
to other objects and to determine means of problem solution or to forecast unknown
properties.
Case-based reasoning , like reasoning by analogy, is based on analogy; however, there are
certain differences in their implementation. In the most encyclopedias, a precedent (from
Latin, precedentis) is defined as a case that took place earlier and is an example or
justification for subsequent events of this kind. Creating a precedent is to give grounds for
similar cases in the future, and establishing a precedent is to find a similar case in the
past.
The generalized structure of a real-time IDSS (RT IDSS) is represented in Fig. 1 [Vagin et al.,
2007].