| 大会名称 |
| 2019年 総合大会 |
| 大会コ－ド |
| 2019G |
| 開催年 |
|
2019
|
| 発行日 |
|
2019-03-05
|
| セッション番号 |
|
BS-4
|
| セッション名 |
|
Compositive Information Communication Technologies and Applications for Future Network Systems
|
| 講演日 |
|
2019/03/20
|
| 講演場所(会議室等) |
|
52号館 104教室
|
| 講演番号 |
|
BS-4-22
|
| タイトル |
|
Future Research Trends by Integrating Deep Reinforcement Learning, Robotics and Game Theory
|
| 著者名 |
|
○Cheng Zhang, Richard T. B. Ma, Bo Gu, Noriaki Kamiyama, Wei Li, Yoshiaki Tanaka,
|
| キーワード |
|
deep, reinforcement, learning, robotics, game, theory
|
| 抄録 |
|
This paper deals with fusion of deep reinforcement learning, robotics and game theory. Common subject, objective, and application of these three techniques are analyzed, and it is expected to strengthen the effect of these three techniques by integrating them in a common framework. To the best our knowledge, it is the first time to consider these three techniques at the same time in this paper. Possible future research directions that integrate deep reinforcement learning, robotics and game theory are also provided.
|
| 本文pdf |
|
PDF download
|
