文献一覧: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (雑誌)

4 0 0 0 ロボットは東大に入れるか? : 国立情報学研究所「人工頭脳」プロジェクト(<特集>ロボットは東大に入れるか?)

著者: 新井紀子松崎拓也 Noriko Arai Takuya Matsuzaki
出版者: 人工知能学会
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.27, no.5, pp.463-469, 2012-09-01
参考文献数: 2
被引用文献数: 1

2019-02-10 22:27:35
4 + 1 Twitter

https://ci.nii.ac.jp/naid/110009496293

4 0 0 0 OA アイロニーはどのように識別されるか : 暗黙的提示に基づくアイロニーの識別モデル

著者: 内海彰 Akira Utsumi 東京工業大学大学院総合理工学研究科知能システム科学専攻 Dept. of Computational Inteligence and Systems Science Tokyo Institute of Technology
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.14, no.4, pp.700-708, 1999-07-01

Although many linguistic and psychological studies have been made on verbal irony, they still cannot distinguish ironic utterances from nonironic ones completely. This paper argues that irony is distinguished from nonirony in accordance with both the ironic environment condition (i.e., irony presupposes a situational setting consisting of the speaker's expectation, incongruity between the expectation and the reality, and the speaker's negative attitude) and the implicit display condition (i.e., irony satisfies at least two of the three features: allusion, pragmatic insincerity and indirect cues). This paper then shows that the argument is empirically supported, especially that ironic environment is a crucial distinctive feature of irony while implicit display suggests a high possibility of irony. It also suggests an interpretation process of irony consistent with these findings.

2017-12-30 16:52:49
4 + 0 Twitter

http://id.nii.ac.jp/1004/00004703/

4 0 0 0 デザインにおける意図と創造性(<特集>意図研究のスペクトル)

著者: 野口尚孝 Hisataka Noguchi
出版者: 一般社団法人人工知能学会
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.20, no.4, pp.379-386, 2005-07-01
参考文献数: 12

2012-06-26 13:25:19
4 + 11 Twitter

3 0 0 0 OA ソーシャルメディアの政治的活用 : 活用事例と分析事例から(<特集>Twitterとソーシャルメディア)

著者: 吉田光男松本明日香 Mitsuo Yoshida Asuka Matsumoto
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.27, no.1, pp.43-50, 2012-01-01

2021-03-12 00:02:38
3 + 7 Twitter

http://id.nii.ac.jp/1004/00007900/

3 0 0 0 OA 深層脳内情報処理から学ぶもの : 機能脳科学の観点から

著者: 苫米地英人 Hideto Tomabechi
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.16, no.2, pp.267-277, 2001-03-01

2021-03-07 00:05:50
2 + 0 Twitter
1 + 1 Wikipedia

http://id.nii.ac.jp/1004/00005195/

3 0 0 0 OA 小論文およびエッセイの自動評価採点における研究動向(<特集>テキストの自動評価)

著者: 石岡恒憲 Tsunenori Ishioka
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.23, no.1, pp.17-24, 2008-01-01

2019-09-23 16:05:51
3 + 0 Twitter

http://id.nii.ac.jp/1004/00006884/

3 0 0 0 OA 牌譜の解析による麻雀の分析(<特集>思考ゲーム)

著者: とつげき東北伊藤毅志 Tohoku Totsugeki Takeshi Ito
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.24, no.3, pp.355-360, 2009-05-01

2019-03-30 10:53:23
2 + 2 Twitter
1 + 1 Wikipedia

http://id.nii.ac.jp/1004/00007260/

3 0 0 0 OA 多様な目的に適した形態素解析システム用電子化辞書(<特集>日本語コーパス)

著者: 伝康晴 Yasuharu Den
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.24, no.5, pp.640-646, 2009-09-01

2018-11-29 17:58:07
3 + 1 Twitter

http://id.nii.ac.jp/1004/00007330/

3 0 0 0 OA HAIのための心理学実験と生体情報 : ユーザを知るということ(<特集>深化するHAI:ヒューマンエージェントインタラクション)

著者: 小松孝徳 Takanori Komatsu 信州大学ファイバーナノテク国際若手研究者育成拠点 International Young Researcher Empowerment Center Shinshu University
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.24, no.6, pp.833-839, 2009-11-01

2017-12-11 14:19:44
3 + 12 Twitter

http://id.nii.ac.jp/1004/00007382/

2021-06-06 11:18:58
2 + 2 Twitter

http://id.nii.ac.jp/1004/00006895/

2 0 0 0 OA 中国語の部屋再考(<特集>チューリングテストを再び考える)

著者: 中島秀之 Hideyuki Nakashima
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.26, no.1, pp.45-49, 2011-01-01

2021-01-06 22:47:22
2 + 4 Twitter

http://id.nii.ac.jp/1004/00007685/

2 0 0 0 OA 状況意味論と談話理解 (<小特集>「状況意味論」)

著者: 片桐恭弘 Yasuhiro Katagiri
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.7, no.3, pp.399-407, 1992-05-01

2020-01-31 13:22:38
2 + 7 Twitter

http://id.nii.ac.jp/1004/00003139/

2 0 0 0 OA 形質の遺伝を重視した遺伝的アルゴリズムに基づく巡回セールスマン問題の解法

著者: 山村雅幸小野貴久小林重信 Masayuki Yamamura Takahisa Ono Shigenobu Kobayashi
雑誌: 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence (ISSN:09128085)
巻号頁・発行日: vol.7, no.6, pp.1049-1059, 1992-11-01

Genetic Algorithms (GA) is a new learning paradigm that models a natural evolution mechanism. The framework of GA straightly corresponds to an optimization problem. They are classified into functional optimization and combinatorial one, and have been studied in different manners. GA can be applied to both types of problems and moreover their combinations. According to generations, GA will discover and accumulate building blocks in the form of schemata, and find the global solution as their combinations. It is said GA can find the global solution rapidly if the population holds sufficient varieties. However, this expectation has not been confirmed rigidly. Indeed, there are some problems pointed out such as the early convergence problem in functional optimization, and the encode/decode-crossover problem in combinatorial one. In this paper, we give a solution to the encode/decode-crossover problem for traveling salesman problems (TSP) with a character-preserving GA. In section 2, we define the encode/decode-crossover problem. The encode-decode problem is to define a correspondence between GA space and problem space. The crossover problem is to define a crossover method in GA space. They are closely related to the performance of GA. We point out some problems with conventional approaches for TSP. We propose three criteria to define better encode/decode ; the completeness, soundness and non-redundancy. We also propose a criterion to define better crossover ; character-preservingness. In section 3, we propose a character-preserving GA. In TSP, good subtours are worth preserving for descendants. We propose a subtour exchange crossover, that will not break subtours as possible. We also propose a compress method to improve efficiency. In section 4, we design an experiment to confirm usefulness of our character-preserving GA. We use a double-circled TSP in which the same numbers of cities are placed on two concentrated circles. There are two kinds of local solutions ; "C"-type and "O"-type. The ratio between outer and inner radius determines which is the optimum solution. We vary the radius ratio and see how much optimal solutions are obtained. In the result, character-preserving GA finds optimal solutions effectively.