Integrating Hybrid Rule-Based
with Case-Based Reasoning

Jim Prentzas and Ioannis Hatzilygeroudis

University of Patras, School of Engineering
Dept of Computer Engin. & Informatics, 26500 Patras, Hellas (Greece)
and
Computer Technology Institute, P.O. Box 1122, 26110 Patras, Hellas (Greece)
{prentzas, ihatz}@ceid.upatras.gr, ihatz@cti.gr



Abstract. In this paper, we present an approach integrating neurule-based and
case-based reasoning. Neurules are a kind of hybrid rules that combine a
symbolic (production rules) and a connectionist representation (adaline unit).
Each neurule is represented as an adaline unit. One way that the neurules can be
produced is from symbolic rules by merging the symbolic rules having the
same conclusion. In this way, the number of rules in the rule base is decreased.
If the symbolic rules, acting as source knowledge of the neurules, do not cover
the full complexities of the domain, accuracy of the produced neurules is
affected as well. To improve accuracy, neurules can be integrated with cases
representing their exceptions. The integration approach enhances a previous
method integrating symbolic rules with cases. The use of neurules instead of
symbolic rules improves the efficiency of the inference mechanism and allows
for drawing conclusions even if some of the inputs are unknown.
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