Name
Abstract | ||
|---|---|---|
This paper describes an evolvable system that has a computational model of basal ganglia and hippocampus which have close relation to the generation and management of memory and movement faculty in our brain. We also describe its application to the design of learnable autonomous mobile robots. From a view point of Evolvable System, first we argue how the particular functions of basal ganglia and hippocampus work for memory and movement. Next a computational model of basal ganglia and hippocampus is presented as a specific type of evolvable systems, and how this model can be used for the design of learnable robots is described. Then we make our actually constructed robot learn, using the implemented model, four fundamental behavior tasks such as those insects learn in their baby stages. It follows with the analysis of the learned behavior. Finally, we discuss the significance of our research. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1007/3-540-63173-9_49 | ICES |
Keywords | Field | DocType |
autonomous robot,biological systems,robot learning,computer model | Robot learning,Social robot,Robot control,Aerospace engineering,Control engineering,Artificial intelligence,Mobile robot navigation,Engineering,Autonomous robot,Robot,Mobile robot,Ubiquitous robot | Conference |
Volume | ISSN | ISBN |
1259 | 0302-9743 | 3-540-63173-9 |
Citations | PageRank | References |
4 | 0.69 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Yamamoto | 1 | 4 | 0.69 |
| Yuichiro Anzai | 2 | 244 | 40.11 |