| Project/Area Number |
14350209
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
System engineering
|
|---|
| Research Institution | Chiba University |
|---|
Principal Investigator |
HIRATA Hironori CHIBA Univ, Graduate school of Science and Technology, Professor, 大学院・自然科学研究科, 教授 (60111415)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
SUGAI Yasuo CHIBA Univ, Dept.of Engineering, Associate Prof., 工学部, 教授 (30187629)
KOAKUTSU Seiichi CHIBA Univ, Graduate school of Science and Technology, Associate Prof., 大学院・自然科学研究科, 助教授 (70241940)
HAMAGAMI Tomoki CHIBA Univ, Graduate school of Science and Technology, Research Associate, 大学院・自然科学研究科, 助手 (30334204)
|
|---|
| Project Period (FY) |
2002 – 2004
|
| Project Status |
Completed (Fiscal Year 2004)
|
| Budget Amount *help |
¥16,500,000 (Direct Cost: ¥16,500,000)
Fiscal Year 2004: ¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2003: ¥4,800,000 (Direct Cost: ¥4,800,000)
Fiscal Year 2002: ¥9,900,000 (Direct Cost: ¥9,900,000)
|
|---|
| Keywords | emergent systems / multiagent / intelligent wheelchair / reinforcement learning / autonomous mobile robots / cooperative behavior / learning automata / 遺伝的プログラミング / 自律行動 / セルオートマトン |
|---|
| Research Abstract |
With comprehensive studies and practical conclusions for "emergent intelligence from intelligent agent team under dynamic environments," this study has been comprehensively examined from a theory construction to a prototype development.
(1)"Intelligent wheelchair," the major theme of this project, has been prototyped with converting commercial electric wheelchair. Under specifications of the prototyped wheelchair, we have succeeded in emergence of intelligent behavior focused on autonomous, cooperative, and collaborative actions from interaction in agent team.
(2)Focusing on "crowd behavior", we conducted fundamental studies of macro-level behavior with intelligent agents. The results of emergence simulation experiments of crowd behavior and traffic flow have shown the phenomenon of autonomous organization and extremely complex behavior which leads to serious accidents.
(3)In each case of simulation or constructive approaches, in order to acquire efficient behavior in dynamic environment, agents need to attach the adaptive learning and evolutionary approach. Developing advanced technique of reinforcement learning and evolutionary algorithm, we have proposed practical techniques which enable agents to acquire intelligent behavior in the intelligent wheelchair control and the niultiagent simulation.
(4)A dynamic configuration system with "Evolutionary hardware," which is the notable trend of recent years, has been developed for enabling agent to have autonomous restoration in the case of fail. The result of the simulation experiment has shown the advantage at a maze problem of an autonomous robot.
As the results of these studies, we confirmed that this project contributed importantly to the accomplishment of both development of fundamental techniques and showing practical applications for establishment of multiagent applications.
|
