Neural-symbolic integration system. #Neural-Symbolic System #Neural Network #Inductive Logic Programming #Connection #Paradigm #Preposition
C-IL2P was developed as an open source C++ implementation of the original C-IL2P system.
C-IL2P was created as a neural-symbolic learning system that makes use of a propositional logic program to build a three-layer recursive neural network. The C-IL2P system can also use back-propagation to learn from examples.
What's new in C-IL2P 1.3 Beta:
- Several new functionalities have been added:
- A novel normalization that maintains C-IL2P building algorithm correctness has been made
- It is possible now to print network weight info after normalization and after training
- Now it is possible to run deduction datasets (no training data) and pure learning problems (no background knowledge data)
C-IL2P 1.3 Beta
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Windows 7
Windows Vista
Windows XP - file size:
- 578 KB
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