There exists a large conceptual gap between symbolic models and emergent models for the
mind. Many emergent models work on low-level sensory data, while many symbolic models …

This paper models a biological brain—excluding motivation (eg, emotions)—as a Finite
Automaton in Developmental Network (FA-in-DN), but such an FA emerges incrementally in …

Bio-inspired strategies for robotic sensing are essential for in situ manufactured sensors on
the Moon. Sensors are one crucial component of robots that should be manufactured from …

The universal Turing Machine (TM) is a model for Von Neumann computers—general-
purpose computers. A human brain, linked with its biological body, can inside-skull …

The human vision system can efficiently recognize multiscale objects in cluttered
backgrounds. The scheme can be achieved with a visual attention mechanism by …

General object recognition in complex backgrounds is still challenging. On one hand, the
various backgrounds, where object may appear at different locations, make it difficult to find …

How and under what circumstances the training effects of perceptual learning (PL) transfer
to novel situations is critical to our understanding of generalization and abstraction in …

Strong AI requires the learning engine to be task non-specific and to automatically construct
a dynamic hierarchy of internal features. By hierarchy, we mean, eg, short road edges and …

Inventors: Juyang Weng, Okemos, MI (US); Zejia Zheng, East Lansing (US); **ang Wu,
Nanking (CN)(73) Assignee: Juyang Weng, Okemos, MI (US)(21) Appl. No.: 16/265,212 (22) …

In autonomous learning, value-sensitive experiences can improve the efficiency of learning.
A learning network needs be motivated so that the limited computational resources and the …