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Abstract: Neurules are a type of hybrid rules combining a symbolic and a connectionist representation. There are two disadvantages of neurules. The first is that the created neurule bases usually contain multiple representations of the same piece of knowledge. Also, the inference mechanism is rather connectionism oriented than symbolism oriented, thus reducing naturalness. To remedy these deficiencies, we introduce an extension to neurules, called multineurules, and an alternative inference process,... (Update)
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BibTeX entry: (Update)
@inproceedings{ hatzilygeroudis02multiinference,
author = "Ioannis Hatzilygeroudis and Jim Prentzas",
title = "Multi-inference with Multi-neurules",
booktitle = "{SETN}",
pages = "30-41",
year = "2002",
url = "citeseer.ist.psu.edu/hatzilygeroudis02multiinference.html" }
Citations (may not include all citations):90 Neural Network Learning and Expert Systems (context) - Gallant - 1993
7 Neurules: Improving the Performance of Symbolic Rules - Hatzilygeroudis, Prentzas - 2000
5 A Recency Inference Engine for Connectionist Knowledge Bases (context) - Ghalwash - 1998
5 An Efficient Hybrid Rule Based Inference Engine with Explana.. - Hatzilygeroudis, Prentzas - 2001
2 XBONE: A Hybrid Expert System for Supporting Diagnosis of Bo.. - Hatzilygeroudis, Vassilakos et al. - 1997
2 Constructing Modular Hybrid Knowledge Bases for Expert Syste.. (context) - Hatzilygeroudis, Prentzas - 2001
1 HYMES: A HYbrid Modular Expert System with Efficient Inferen.. - Hatzilygeroudis, Prentzas - 2001
ftp://ftp.ics.uci.edu/pub/machine-learning-databases/
Documents on the same site (http://mmlab.ceid.upatras.gr/aigroup/ihatz/ihatz-publications.html): More
Neurules: Integrating Symbolic Rules and Neurocomputing - Hatzilygeroudis, Prentzas (2000) (Correct)
A Web-Based ITS Controlled by an Expert System - Prentzas, Hatzilygeroudis.. (2001) (Correct)
Constructing Modular Hybrid Rule Bases for Expert Systems - Hatzilygeroudis, Prentzas (2001) (Correct)
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