| Project/Area Number |
25420212
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Intelligent mechanics/Mechanical systems
|
|---|
| Research Institution | Tokyo Institute of Technology |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2013-04-01 – 2016-03-31
|
| Project Status |
Completed (Fiscal Year 2015)
|
| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
|
|---|
| Keywords | 匂い源探索 / 状況依存性 / 情報エントロピー / 飛翔筋位相差 / サーボスフィア / ベイズ推定 / カイコガ / 光遺伝的手法 |
|---|
| Outline of Final Research Achievements |
In this study, we investigated state-dependent decision making algorithms of a silkworm moth and replayed the results in simulation environments. We proposed and build a novel experimental system named 3D-servo sphere, by which we could observe behaviors of the animal without any fixations. We also established methods to measure neural responses of flight muscles and a brain simultaneously. As the result, we found state dependent visual feedbacks during programmed behavior, a set of fixed sequence of actions. When the animal could expect reduction of information entropy, it exhibited movements different from those of the programmed behavior. However, when it could not, it behaved like the programmed behavior. We implemented the policy switching into artificial agent in simulator and carried out simulations in different conditions. As the results, we found the policy switching improved adaptability against variations of the conditions.
|
