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Behavioral Decision Based on Abstraction of Pheromone Distribution for Transport Vehicles
http://hdl.handle.net/2237/6919
http://hdl.handle.net/2237/6919984767cc-b2cc-4b84-98a8-05032763df4c
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
ICTAI_05_679.pdf (625.8 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||
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| 公開日 | 2006-09-11 | |||||
| タイトル | ||||||
| タイトル | Behavioral Decision Based on Abstraction of Pheromone Distribution for Transport Vehicles | |||||
| 言語 | en | |||||
| 著者 |
Mukai, Naoto
× Mukai, Naoto× Watanabe, Toyohide× Jun, Feng |
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| アクセス権 | ||||||
| アクセス権 | open access | |||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
| 権利 | ||||||
| 言語 | en | |||||
| 権利情報 | Copyright © 2005 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | In this paper, we focus on behavioral decisions for empty transport veicles e.g., they shoud wait on their place or go to other places. Effective behaviors of empty vehicles enable to decrease waiting times of customers. Our algorithm to acquire such effective behaviors is based on transport experiences of vehicles (i.e., history). It means that vehicles adjust to their city environment by learning trends of transport demands (e.g., amounts and directions). Our algorithm consists of learning and abstraction stages. In the learning stage, vehicles acquire low-level rules of actions at an intersection. In the abstraction stage, vehicles acquire high-level rules of actions in a region. Finally, we report simulation results and show the effectiveness of our algorithm. | |||||
| 言語 | en | |||||
| 出版者 | ||||||
| 出版者 | IEEE | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプresource | http://purl.org/coar/resource_type/c_6501 | |||||
| タイプ | journal article | |||||
| 出版タイプ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| DOI | ||||||
| 関連タイプ | isVersionOf | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.1109/ICTAI.2005.45 | |||||
| 書誌情報 |
en : 17th IEEE International Conference on Tools with Artificial Intelligence p. 679-680, 発行日 2005-11 |
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| フォーマット | ||||||
| 値 | application/pdf | |||||
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| 値 | publisher | |||||
| URI | ||||||
| 識別子 | http://hdl.handle.net/2237/6919 | |||||
| 識別子タイプ | HDL | |||||
