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Leabra

Leabra stands for Local, Error-driven and Associative, Biologically Realistic Algorithm. It is a model of learning which is a balance between Hebbian… 
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Related topics

Related topics

11 relations
Almeida–Pineda recurrent backpropagationComputer simulationEmergentError-driven learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Functional Role of Neural Oscillations in Attentional Inhibition and Long Term Memory Retrieval
2016
2016
A LEABRA Framework for Sequence Alignment Problem using Emergent
Sequence alignment is highly important procedure for alignment of DNA sequences or RNA sequences or some other biological protein… 
2014
2014
Modeling the Serial Position Effect - Using the Emergent Neural Network Simulation System
The Serial Position Effect (SPE) is a well-studied phenomenon in experimental psychology. SPE captures the idea that, when… 
Review
2013
Review
2013
Neurocomputational Models of Face Processing
Until the day we can record from multiple neurons in undergraduates, understanding how humans process faces requires an… 
2013
2013
Integrating top-down expectations with bottom-up perceptual processing in a hybrid neural-symbolic architecture
2011
2011
A Metacognitive Classifier Using a Hybrid ACT-R/Leabra Architecture
We present a metacognitive classifier implemented within a hybrid architecture that combines the strengths of two existing… 
2010
2010
Integrated Cognitive Architectures For Robust Decision Making
Abstract : Introduction The project s goal was to reproduce robust and intelligent decision making capabilities in artificial… 
Review
2007
Review
2007
Computational Cognitive Neuroscience Modeling Using Leabra In PDP
Computational Cognitive Neuroscience Modeling Using Leabra In PDP++ David C. Noelle (dnoelle@ucmerced.edu) University of… 
2004
2004
Generalization and Discrimination in a Semantic Network Trained with Semi-Supervised Learning
The goal of the proposed research is to explore semantic learning in an artificial neural network trained with a semi-supervised… 
2003
2003
Multilevel Computational Modeling of Human Attentional Networks
Suppose a student S was asked to solve the equation “2x + 3 = 9”. After 2 seconds, he gave the answer “x = 3”. Both cognitive… 
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