NeuroLISP: High-level symbolic programming with attractor neural networks.
Gregory P. DavisGarrett E. KatzRodolphe J. GentiliJames A. ReggiaPublished in: Neural Networks (2022)
Keyphrases
- high level
- neural network
- programming language
- low level
- cellular automata
- connectionist models
- connectionist systems
- neural learning
- intermediate level
- symbolic knowledge
- pattern recognition
- fuzzy logic
- artificial neural networks
- dynamical systems
- fixed point
- neural network model
- low level features
- back propagation
- programming environment
- lower level
- symbolic reasoning
- connectionist learning
- dynamic behavior
- neural nets
- phase space
- object oriented programming
- network architecture
- training process
- recurrent neural networks
- conceptual model
- symbolic representation
- development environment
- computer programming
- fuzzy systems
- programming course
- multi layer
- database
- fault diagnosis
- source code
- computational intelligence
- object oriented
- data sets