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Keywords
(2)
Artificial Neural Network
Inductive Learning
Related Publications
(3)
The Connectionist Inductive Learning and Logic Programming System
Extracting Refined Rules from KnowledgeBased Neural Networks
Towards a New Massively Parallel Computational Model for Logic Programming
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Logical inference and inductive learning in artificial neural networks
Logical inference and inductive learning in artificial neural networks,S. D Artur,Gerson Zaverucha,Luis A. V. De Carvalho
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Logical inference and inductive learning in artificial neural networks
(
Citations: 12
)
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S. D Artur
,
Gerson Zaverucha
,
Luis A. V. De Carvalho
Published in 1997.
Cumulative
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Citation Context
(8)
...As [26] employed binary threshold units as activation functions of the network nodes, the results were lifted to sigmoidal and hence differentiable activation functions in [
20
, 19]...
Jens Lehmann
,
et al.
Extracting reduced logic programs from artificial neural networks
...A combined approach was finally presented in [
4
], allowing an intuitive onetoone transformation of propositional logic to neural nets while maintaining learning capabilities...
Daniel Michulke
,
et al.
Neural Networks for State Evaluation in General Game Playing
...This problem was solved in [
13
] by showing that the same results can be achieved if bipolar sigmoidal units are used instead...
...[
13
] also overcomes a restriction of the KBANN method originally presented in [35]: rules may now have arbitrarily many preconditions and programs may have arbitrarily many rules with the same postcondition...
...While it was shown in [
13
], that the propositional core method leads to improved training behaviour, it is important to notice that propositional logic is in general insucient for knowledge based intelligent systems...
Sebastian Bader
,
et al.
Connectionist Model Generation: A FirstOrder Approach
...This problem was solved in [
11
] by showing that the same results can be achieved if bipolar sigmoidal units are used instead (see also [8])...
...[
11
] also overcomes a restriction of the KBANN method originally presented in [32]: rules may now have arbitrarily many preconditions and programs may have arbitrarily many rules with the same postcondition...
Sebastian Baderand
,
et al.
The Core Method: Connectionist Model Generation
...There were several attempts to make these neural networks more “intelligent”, see, for example, [5], [
6
], [7] for some further developments...
Ekaterina Komendantskaya
.
Learning and deduction in neural networks and logic
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Citations
(12)
Extracting reduced logic programs from artificial neural networks
(
Citations: 6
)
Jens Lehmann
,
Sebastian Bader
,
Pascal Hitzler
Journal:
Applied Intelligence  APIN
, vol. 32, no. 3, pp. 249266, 2010
Neural Networks for State Evaluation in General Game Playing
Daniel Michulke
,
Michael Thielscher
Conference:
Principles of Data Mining and Knowledge Discovery  PKDD
, pp. 95110, 2009
Connectionist Model Generation: A FirstOrder Approach
(
Citations: 9
)
Sebastian Bader
,
Pascal Hitzler
,
Steen Holldobler
Journal:
Neurocomputing  IJON
, 2007
The Core Method: Connectionist Model Generation
(
Citations: 5
)
Sebastian Baderand
,
Steffen Hölldobler
Conference:
Int. Conference on Artificial Neural Networks  ICANN
, pp. 113, 2006
Learning and deduction in neural networks and logic
(
Citations: 6
)
Ekaterina Komendantskaya
Published in 2006.