Name
Abstract | ||
|---|---|---|
Our group has constructed a series of brain-based devices (BBDs); i.e. physical devices with simulated nervous systems that guide behavior, to serve as a heuristic for understanding brain function. Unlike conventional robots designed by engineering principles, BBDs are based on biological principles and alter their behavior to the environment through self-learning. The resulting systems autonomously generalize signals from the environment into perceptual categories and through adaptive behavior become increasingly successful in coping with the environment. Although the principal focus of developing BBDs has been to test theories of the nervous system, this approach may also provide a basis for robotic design and practical applications. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/IROS.2003.1250749 | IROS 2003: PROCEEDINGS OF THE 2003 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4 |
Keywords | Field | DocType |
neurophysiology,unsupervised learning,adaptive behavior,mobile robots,nervous system | Heuristic,Neurophysiology,Intelligent decision support system,Computer science,Control engineering,Unsupervised learning,Artificial intelligence,Robot,Adaptive behavior,Perception,Mobile robot | Conference |
Citations | PageRank | References |
11 | 1.09 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeffrey L. Krichmar | 1 | 443 | 41.97 |
| Gerald M. Edelman | 2 | 190 | 19.26 |