| Presentation | 2021-02-22 A Study on the Application of Curriculum Learning in Deep Reinforcement Learning Ikumi Kodaka, Fumiaki Saito, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Deep reinforcement learning is attracting attention because it can be applied to higher-dimensional environments compared to conventional reinforcement learning. However, an important issue is to increase the number of trials required for action acquisition, particularly in high-dimensional and sparsely rewarded tasks. Therefore, in this study, we applied curriculum learning, which improves learning performance by gradually changing the difficulty level of tasks, in the action acquisition in a shooting game AI. Through experimental evaluation, we verified the speeding up of action acquisition and considered the transition of difficulty and its efficiency. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep Reinforcement Learning / Curriculum Learning / Deep Q-Network / Game AI |
| Paper # | AI2020-47 |
| Date of Issue | 2021-02-15 (AI) |
| Conference Information | |
| Committee | AI |
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| Conference Date | 2021/2/22(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Web/IoT Intelligence, etc. |
| Chair | Naoki Fukuta(Shizuoka Univ.) |
| Vice Chair | Yuichi Sei(Univ. of Electro-Comm.) / Yuko Sakurai(AIST) |
| Secretary | Yuichi Sei(Nagoya Inst. of Tech.) / Yuko Sakurai(Tokyo Univ. of Agriculture and Technology) |
| Assistant | |
| Paper Information | |
| Registration To | Technical Committee on Artificial Intelligence and Knowledge-Based Processing |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on the Application of Curriculum Learning in Deep Reinforcement Learning |
| Sub Title (in English) | action acquisition in shooting game AI as an example |
| Keyword(1) | Deep Reinforcement Learning |
| Keyword(2) | Curriculum Learning |
| Keyword(3) | Deep Q-Network |
| Keyword(4) | Game AI |
| 1st Author's Name | Ikumi Kodaka |
| 1st Author's Affiliation | Chiba Institute of Technology(CIT) |
| 2nd Author's Name | Fumiaki Saito |
| 2nd Author's Affiliation | Chiba Institute of Technology(CIT) |
| Date | 2021-02-22 |
| Paper # | AI2020-47 |
| Volume (vol) | vol.120 |
| Number (no) | AI-379 |
| Page | pp.pp.47-52(AI), |
| #Pages | 6 |
| Date of Issue | 2021-02-15 (AI) |