{"id":1008208,"date":"2018-02-02T18:54:39","date_gmt":"2018-02-02T09:54:39","guid":{"rendered":"http:\/\/www2017renew.ai-gakkai.or.jp\/en\/?p=1008208"},"modified":"2021-05-18T17:58:27","modified_gmt":"2021-05-18T08:58:27","slug":"vol33_no1","status":"publish","type":"page","link":"https:\/\/www.ai-gakkai.or.jp\/en\/published_books\/journals_of_jsai\/past_journals\/in2018\/vol33_no1\/","title":{"rendered":"Artificial Intelligence Vol. 33 No.1 (Jan. 2018)"},"content":{"rendered":"

Commentary<\/strong>
\nInteraction with Next Generation AI Researchers \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Ryohei Orihara 1<\/p>\n

Article<\/strong>
\nCover Comment: UME \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 UME and Youichiro Miyake 2
\nExperiential Entertainment and Artificial Intelligence
\n\u2500 How to Slove the Missions in 2017 \u2500 \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Yusuke Takeuchi 4<\/p>\n

Special Issue:\u201cComputing Resources for AI\u201d<\/strong>
\nEditors\u2019 Introduction to\u201cComputing Resources for AI\u201d \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Satoshi Ueno, Koichi Takahashi and Hidemoto Nakada 5
\nConstruction of Cloud Infrastructure for AI and Big Data Processing
\n\u2500 AIST AI Cloud\uff08AAIC\uff09 and AI Bridging Cloud Infrastructure\uff08ABCI\uff09\u2500 \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hirotaka Ogawa 8
\nUtilizing Public Cloud Services for Artificial Intelligence \/ Machine Learning Research and Applications \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Hidemoto Nakada 15
\nDeep Learning Chips and AI Computing \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hiroshi Momose and Tetsuya Asai 23
\nA Trand of the Deep Learning Research and Development for an FPGA \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hiroki Nakahara 31
\nBrain-like Analog Computing and Dedicated Integrated Circuits \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Takashi Morie 39
\nA Data Management Infrastructure for Intelligent Systems
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026Antonello Ceravola, Frank Joublin, Heiko Wersing, Stephan Hasler, Behzad Dariush and Yi-Ting Chen 45<\/p>\n

Special Issue:\u201cIntroduction to Special Issue on JSAI Incentive Award 2016\u201d<\/strong>
\nEditors\u2019 Introduction to\u201cIntroduction to Special Issue on JSAI Incentive Award 2016\u201d \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Toshikazu Fukushima 55
\nFPAI: Applying Permutation Decision Diagrams to Cycle Type Partition on a Permutation Set
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Yuma Inoue and Shin-ichi Minato 57
\nFPAI: A CSP Approach for Laboratory Assignment Problems with Partial Order on Student\u2019s Preference
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Tatsuki Fujii, Yasunobu Itou and Hidetomo Nabesima 58
\nKBS: Proposition of Kernelized Evolutionary Distance Metric Learning for Semi-supervised Clustering
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Kalintha Wasin, Satoshi Ono, Masayuki Numao and Ken-ichi Fukui 60
\nSLUD: Modeling of Intention in Discussion and Prototyping of Interactive Minutes Generation System while
\nRepeatedly Question-Answering \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hiroya Miura, Yoshinari Takagawa and Keiji Hirata 62
\nALST: Development and Evaluation of Exercises System of a Three-way Logic Assembly Activities using the Triangle Logic Model
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Takuya Kitamura, Hironari Hase, Kazushige Maeda, Yusuke Hayashi and Tsukasa Hirashima 63
\nChallenge: Controlling Actions with Pruning in RoboCup Soccer \u2026\u2026\u2026\u2026\u2026\u2026\u2026 Sho Tanaka, Tomoharu Nakashima and Hidehisa Akiyama 65
\nLSE: Evaluation of a Topic-Sensitive Dialog System Integrated with Pun Humor \u2026\u2026\u2026\u2026\u2026\u2026 Motoki Yatsu and Kenji Araki 67
\nLSE: Study of a Serious Game for Learning Communication with Autism Including Miscomprehension of Nuance
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Keigo Yabuki and Kaoru Sumi 68
\nSAI: Analysis and Visualization of ID-POS Data How Purchasing Behavior Changes along with Annual Seasons
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Nami Harada, Kazuya Yamashita and Yoichi Motomura 69
\nFIN: Artificial Intelligence Predictor for Multivariate Time Series with Deep-learning and Wavelet Analysis\u2026\u2026\u2026\u2026\u2026\u2026\u2026Takashi Shiono 71
\nKST: Methodology for Knowledge Acquisition of Various Aged Care Process from Each Care Facility
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Satoshi Nishimura, Hiroshi Ohtani, Naoto Hatakeyama, Kieko Hasebe, Ken Fukuda,
\nYoshinobu Kitamura, Riichiro Mizouchi and Takuichi Nishimura 72
\nKSN: Consideration of Global Communication Process through Enterprise Portal
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Yoshimasa Masuda, Shuichiro Yamamoto and Seiko Shirasaka 74
\nSWO: Predicting Relations of Embedded RDF Entities by Deep Neural Network
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Yohei Onuki, Shun Nukui, Tsuyoshi Murata, Seiya Inagi, Xule Qiu, Hiroshi Okamoto and Masao Watanabe 75
\nDOCMAS: Agent-based Modeling and Simulation of Public Transport Vehicles based on Probe-Car Data
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hiroaki Kingetsu and Hiromitsu Hattori 77
\nBI: Simulation on the Effect of Financial Regulation on Stability of Financial System and Financial Institution Behavior
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Takamasa Kikuchi, Masaaki Kunigami, Takashi Yamada, Hiroshi Takahashi and Takao Terano 79
\nAIMED: Cerebral Aneurysm Occurrence Prediction by Morphometric Analysis of the Willis Ring
\n\u2026\u2026\u2026\u2026\u2026 Marin Yasugi, Belayat M. Hossain, Hironobu Shibutani, Tamotsu Nomura, Manabu Nii, Masakazu Morimoto and Syoji Kobashi 81
\nAM: Related Term Suggestion using Cooking Recipe Document Structure and Its Application to Interactive Query Expansion
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Michiko Yasukawa 82
\nAGI: Qualitative Description for Brain Function Generating Negative Emotion against Facial Expression of Humanlike Agent
\n\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Tawatsuji Yoshimasa and Matsui Tatsunori 84<\/p>\n

Special Issue:\u201cNew Trends of Researches for Doctorial Theses\u201d<\/strong>
\nEditors\u2019Introduction to\u201cNew Trends of Researches for Doctorial Theses\u201d \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Tomonobu Ozaki, Hidenori Kawamura and Hiroyuki Shindo 86
\nFundamentals of AI\u300087 \uff0f Machine Learning and Data Mining\u300088 \uff0f Knowledge Use and Sharing\u300088 \uff0f Web Intelligence\u300089 \uff0f
\nSemantic Web and Natural Language Processing\u300090 \uff0f Soft Computing\u300090 \uff0f Natural Language Processing\u300091 \uff0f
\nHuman Interface and Computer \u2013 Supported Systems\u300091 \uff0f AI Applications\u300092<\/p>\n

Special Issue:\u201cIntelligent Dialogue Systems\u201d<\/strong>
\nEditors\u2019Introduction to\u201cIntelligent Dialogue Systems\u201d \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Ryuichiro Higashinaka and Shogo Okada 93<\/p>\n

Lecture Series:\u201cSingularity and AI\u201d\uff084\uff09<\/strong>
\nAI Will Accelerate Exponentially But Singularity Is Not Near \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hideyuki Nakashima 95<\/p>\n

My Bookmark<\/strong>
\nFood Information Processing \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Jun Harashima 98<\/p>\n

Opinion Box<\/strong>
\nOpinion Box for Reader-Editor Interaction \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hirotaka Osawa, Naho Orita and Kouichi Takahashi 102<\/p>\n","protected":false},"excerpt":{"rendered":"

Commentary Interaction with Next Generation AI Researchers \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Ryohei Orihara 1 Article Cover Comment: UME \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 UME and Youichiro Miyake 2 Experiential Entertainment and Artificial Intelligence \u2500 How to Slove the Missions in 2017 \u2500 \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Yusuke Takeuchi 4 Special Issue:\u201cComputing Resources for AI\u201d Editors\u2019 Introduction to\u201cComputing Resources for AI\u201d \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Satoshi Ueno, Koichi Takahashi and Hidemoto Nakada 5 Construction of Cloud Infrastructure for AI and Big Data Processing \u2500 AIST AI Cloud\uff08AAIC\uff09 and AI Bridging Cloud Infrastructure\uff08ABCI\uff09\u2500 \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hirotaka Ogawa 8 Utilizing Public Cloud Services for Artificial Intelligence \/ Machine Learning Research and Applications \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026Hidemoto Nakada 15 Deep Learning Chips and AI Computing \u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026\u2026 Hiroshi Momose and Tetsuya Asai 23 […]<\/p>\n","protected":false},"author":17,"featured_media":0,"parent":1008870,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"categories":[11],"_links":{"self":[{"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/pages\/1008208"}],"collection":[{"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/users\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/comments?post=1008208"}],"version-history":[{"count":18,"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/pages\/1008208\/revisions"}],"predecessor-version":[{"id":1008252,"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/pages\/1008208\/revisions\/1008252"}],"up":[{"embeddable":true,"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/pages\/1008870"}],"wp:attachment":[{"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/media?parent=1008208"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ai-gakkai.or.jp\/en\/wp-json\/wp\/v2\/categories?post=1008208"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}