| Presentation | 1999/1/11 Learning Causality on Action Language A Hidetomo Nabeshima, Katsumi Inoue, Hiromasa Haneda, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Autonomous agents that behave in dynamic world needs the learning ability that can acquire knowledge about the environment in which the agents have never encountered. In this paper, we investigate a learning algorithm which produces rules about effects of actions from observations in action language A. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Action languages / learning causality / decision tree |
| Paper # | AI98-67 |
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| Conference Information | |
| Committee | AI |
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| Conference Date | 1999/1/11(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Learning Causality on Action Language A |
| Sub Title (in English) | |
| Keyword(1) | Action languages |
| Keyword(2) | learning causality |
| Keyword(3) | decision tree |
| 1st Author's Name | Hidetomo Nabeshima |
| 1st Author's Affiliation | Graduate School of Science and Technology, Kobe University() |
| 2nd Author's Name | Katsumi Inoue |
| 2nd Author's Affiliation | Graduate School of Science and Technology, Kobe University : Department of Electrical and Electronics Engineering, Faculty of Engineering, Kobe University |
| 3rd Author's Name | Hiromasa Haneda |
| 3rd Author's Affiliation | Graduate School of Science and Technology, Kobe University : Department of Electrical and Electronics Engineering, Faculty of Engineering, Kobe University |
| Date | 1999/1/11 |
| Paper # | AI98-67 |
| Volume (vol) | vol.98 |
| Number (no) | 498 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |