Biological neural network models whereby brains make minds help to understand
autonomous adaptive intelligence. This article summarizes why the dynamics and emergent …

Recognizing the actions, plans, and goals of a person in an unconstrained environment is a
key feature that future robotic systems will need in order to achieve a natural human …

Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

In the domain of machine learning, Neural Memory Networks (NMNs) have recently
achieved impressive results in a variety of application areas including visual question …

This article describes neural models of attention. Since attention is not a disembodied
process, the article explains how brain processes of consciousness, learning, expectation …

This article presents an adaptive resonance theory predictive mapping (ARTMAP) model,
which uses incremental cluster validity indices (iCVIs) to perform unsupervised learning …

Abstract “Open world” environments are those in which novel objects, agents, events, and
more can appear and contradict previous understandings of the environment. This runs …

Validation is one of the most important aspects of clustering, particularly when the user is
designing a trustworthy or explainable system. However, most clustering validation …

Biclustering is a powerful tool for exploratory data analysis in domains such as social
networking, data reduction, and differential gene expression studies. Topological learning …

With the maturation of autonomous driving technology, the use of autonomous vehicles in a
socially acceptable manner has become a growing demand of the public. Human-like …