Distributed ART

A real-time model of parallel distributed pattern learning that permits fast as well as slow adaptation, without catastrophic forgetting.


Articles & Tech Transfers


ART and ARTMAP neural networks for applications: Self-organizing learning, recognition, and prediction
Abstract ART and ARTMAP neural networks for adaptive recognition and prediction have been applied to a variety of problems. Applications include parts design retrieval at the Boeing Company, automatic mapping from remote sensing ...

Distributed learning, recognition, and prediction by ART and ARTMAP neural networks
Abstract A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning ...

Distributed activation, search, and learning by ART and ARTMAP neural networks
Abstract A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning ...

Brain categorization:  learning, attention, and consciousness
Abstract How do humans and animals learn to recognize objects and events? Two classical views are that exemplars or prototypes are learned. A hybrid view is that a mixture, called rule-plus-exceptions, is learned. None of these ...

Distributed ARTMAP: a neural network for fast distributed supervised learning
Abstract Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off-line learning to avoid ...

ART neural networks for remote sensing image analysis
Abstract ART and ARTMAP neural networks for adaptive recognition and prediction have been applied to a variety of problems, including automatic mapping from remote sensing satellite measurements, parts design retrieval at the Boeing ...

Distributed ARTMAP
Abstract Distributed coding at the hidden layer of a multi?layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off?line learning to avoid ...

Combining distributed and localist computations in real-time neural networks
Abstract In order to benefit from the advantages of localist coding neural models that feature winner-take-all representations at the top level of a network hierarchy must still solve the computational problems inherent in ...

Adaptive resonance: an emerging neural theory of cognition
Abstract Adaptive resonance is a theory of cognitive information processing which has been realized as a family of neural network models. In recent years, these models have evolved to incorporate new capabilities in the cognitive, ...

ART neural networks for medical data analysis and fast distributed learning
Abstract ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, ...

Neural-network models of learning and memory: leading questions and an emerging framework
Abstract Real-time neural-network models provide a conceptual framework for formulating questions about the nature of cognition, an architectural framework for mapping cognitive functions to brain regions, a semantic framework for ...


Software


SOARD algorithm
Description The Self-Organizing ARTMAP Rule Discovery (SOARD) system derives relationships among recognition classes during online learning. SOARD training on input/output pairs produces direct recognition of individual class labels for ...