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Search DetailsHIRAYAMA KatsutoshiGraduate School of Maritime Sciences / Department of Maritime SciencesProfessor
Researcher basic information
■ Research Keyword■ Research Areas
- Aerospace, marine, and maritime Engineering / Marine and maritime engineering
- Informatics / Intelligent informatics
- Feb. 2023 - Jun. 2023, 14th Workshop on Optimization and Learning in Multiagent Systems, プログラム委員
- Aug. 2022 - Jun. 2023, 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), PC member
- Jul. 2022 - Jun. 2023, 15th International Conference on Marine Navigation and Safety of Sea Transportation (TransNav 2023), PC member
- Aug. 2021 - Mar. 2022, 36th AAAI Conference on Artificial Intelligence (AAAI 2022), Senior PC member
- Apr. 2021 - Oct. 2021, 19th International Conference on Practical Applications of Agents and Multi-agent Systems (PAAMS 2021), PC member
- Mar. 2021 - Jul. 2021, 10th International Congress on Advanced Applied Informatics (IIAI AAI 2021), PC member
- Apr. 2020 - Jun. 2021, 14th International Conference on Marine Navigation and Safety of Sea Transportation (TransNav 2021), PC member
- 電子情報通信学会, 人工知能と知識処理研究会専門委員
Research activity information
■ Award- Feb. 2022 5th Symposium on Multi Agent Systems for Harmonization 2022(SMASH22 Winter Symposium), 奨励賞, 深層強化学習による最適な分散衝突回避
- Mar. 2019 情報処理学会第81回全国大会, 学生奨励賞, 速度制御を考慮に入れた分散衝突回避アルゴリズムJapan society
- Dec. 2018 第17回科学技術フォーラム (FIT-2018), FIT2018 船井ベストペーパー賞受賞, エージェントのタイプに基づく確率的提携構造形成問題Japan society
- Nov. 2018 The 21st International Conference on Principles and Practice of Multi- Agent Systems (PRIMA-2018), Best Paper Award, Bounded Approximate Algorithm for Probabilistic Coalition Structure GenerationInternational society
- Sep. 2015 日本ソフトウェア科学会, 日本ソフトウェア科学会2014年度基礎研究賞, 分散制約最適化問題に関する研究Japan society
- May 2010 International Foundation for Autonomous Agents and Multiagent Systems, IFAAMAS 2010 Influential Paper Award, Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems
- Corresponding, Oct. 2024, Proceedings of Asia Navigation Conference 2024 (ANC-2024), 254 - 264, EnglishWaterway traffic situation awareness based on multi-modal data fusion of smart buoys[Refereed]International conference proceedings
- Mar. 2024, 情報処理学会第86回全国大会講演論文集, Japaneseロバストな警備員配置問題Symposium
- Japanese Society for Artificial Intelligence, Nov. 2023, Transactions of the Japanese Society for Artificial Intelligence, 38(6) (6), A - N31_1, Japanese[Refereed]Scientific journal
- Last, Jun. 2023, 2023年度人工知能学会全国大会(第37回) (JSAI-2023) 講演論文集, Japaneseサービス付き提携構造形成に基づくタクシー相乗り問題Symposium
- In this study, we propose a real-time ship anomaly detection method driven by Automatic Identification System (AIS) data. The method uses ship trajectory clustering classes as a normal model and a deep learning algorithm as an anomaly detection tool. The method is divided into three main steps: (1) quality maintenance of the original AIS data, (2) extraction of normal ship trajectory clusters using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), in which a segmented improved Dynamic Time Warping (DTW) algorithm is used to measure the degree of trajectory similarity, (3) the clustering results are used as a normative model to train a Bi-directional Gated Recurrent Unit (BiGRU) recurrent neural network, which is used as a trajectory predictor to achieve real-time ship anomaly detection. Experiments were conducted using real AIS data from the port of Tianjin, China. The experimental results are manifold. Firstly, the data pre-processing process effectively improves the quality of raw AIS data. Secondly, the ship trajectory clustering model can accurately classify the traffic flow of different modes in the sea area. Moreover, the trajectory prediction result of the BiGRU model has the smallest error with the actual ship trajectory and has a better trajectory prediction performance compared with the Long Short-Term Memory Network model (LSTM) and Gated Recurrent Unit (GRU). In the final anomaly detection experiment, the detection accuracy and timeliness of the BiGRU model are also higher than LSTM and GRU. Therefore, the proposed method can achieve effective and timely detection of ship anomalous behaviors in terms of position, heading and speed during ship navigation, which provides insight to enhance the intelligence of marine traffic supervision and improve the safety of marine navigation.MDPI AG, Mar. 2023, Journal of Marine Science and Engineering, 11(4) (4), 763 - 763, English[Refereed]Scientific journal
- Corresponding, Mar. 2023, 情報処理学会第85回全国大会講演論文集, Japanese推定到達時間の局所同期に基づく適応型ルーティングアルゴリズムSymposium
- Institute of Electronics, Information and Communications Engineers (IEICE), Dec. 2022, IEICE Transactions on Information and Systems, E105.D(12) (12), 2085 - 2091, English[Refereed]Scientific journal
- Corresponding, Sep. 2022, 第21回情報科学技術フォーラム(FIT-2022)講演論文集, Japanese深層強化学習による最適な分散衝突回避Symposium
- Corresponding, Sep. 2022, 第21回情報科学技術フォーラム(FIT-2022)講演論文集, Japanese飛行禁止区域を考慮したトラックおよびドローンの併用による配送計画問題Symposium
- Corresponding, Sep. 2022, 第21回情報科学技術フォーラム(FIT-2022)講演論文集, Japanese回収と配達の両方に時間枠をもつMAPDSymposium
- Last, Sep. 2022, 第21回情報科学技術フォーラム(FIT-2022)講演論文集, EnglishInfluential Variables in Constraint NetworksSymposium
- The container ship stowage planning problem (CSPP) is a very complex and challenging issue concerning the interests of shipping companies and ports. This article has developed a many-objective CSPP solution that optimizes ship stability and reduces the number of shifts over the whole route while at the same time considering realistic constraints such as the physical structure of the ship and the layout of the container yard. Use the initial metacentric height (GM) along with the ship’s heeling angle and trim to measure its stability. Meanwhile, use the total amount of relocation in the container terminal yard, the voluntary shift in the container ship’s bay, and the necessary shift of the future unloading port to measure the number of shifts on the whole route. This article proposes a variant of the nondominated sorting genetic algorithm III (NSGA-III) combined with local search components to solve this problem. The algorithm can produce a set of non-dominated solutions, then decision-makers can choose the best practical implementation based on their experience and preferences. After carrying out a large number of experiments on 48 examples, our calculation results show that the algorithm is effective compared with NSGA-II and random weighted genetic algorithms, especially when applied to solve many-objective CSPPs.MDPI AG, Apr. 2022, Journal of Marine Science and Engineering, 10(4) (4), 517 - 517[Refereed]Scientific journal
- Aug. 2021, Sensors, 21(16) (16)Vessel Scheduling Optimization Model Based on Variable Speed in a Seaport with One-Way Navigation Channel
- Springer Science and Business Media LLC, Apr. 2021, Autonomous Agents and Multi-Agent Systems, 35(1) (1)Scientific journal
- Last, Dec. 2020, 電子情報通信学会論文誌, Vol.J103-D(No.12) (No.12), 853 - 859, Japaneseエージェントのタイプを用いた特性関数の簡略表記法に基づく制限付き提携構造形成問題[Refereed]
- Sep. 2020, 第19回情報科学技術フォーラム(FIT-2020)講演論文集輸送容量ネットワークによる鉄道貨物輸送の頑健性評価 ―貨物集約時のJR貨物各駅の保管/中継機能に着目して―
- Jul. 2020, Annals of Mathematics and Artificial Intelligence, 88(7) (7), 691 - 715[Refereed]Scientific journal
- Jun. 2020, 2020年度人工知能学会全国大会(第34回) (JSAI-2020) 講演論文集U12バスケットボールリーグ戦におけるブレーク数最小化問題
- Jun. 2020, 2020年度人工知能学会全国大会(第34回) (JSAI-2020) 講演論文集分散確率的探索アルゴリズムDSSA+の3次元空間への拡張
- Jun. 2020, 2020年度人工知能学会全国大会(第34回) (JSAI-2020) 講演論文集移動回数制限付きマルチエージェント経路発見問題の新しい定式化と解法
- Apr. 2020, Autonomous Agent Multi-Agent Systems, 34(1) (1)Two Approximation Algorithms for Probabilistic Coalition Structure Generation with Quality Bound[Refereed]
- Mar. 2020, 情報処理学会第82回全国大会講演論文集, Japanese提携値の上下界を利用する提携構造形成アルゴリズムSymposium
- Feb. 2020, 電子情報通信学会和文論文誌D, J103-D(2) (2), 42 - 51, Japaneseエージェントのタイプを用いた特性関数の簡略表記法に基づく確率的提携構造形成問題[Refereed]Scientific journal
- Last, Dec. 2019, Proceedings of the 20th International Symposium on Advanced Intelligent Systems (ISIS 2019), EnglishIdentifying Influential Variables in CSP[Refereed]Symposium
- Oct. 2019, 情報処理学会論文誌, 60(10) (10), 1603 - 1616, Japanese最短経路探索問題のための動的計画法へのコスト平準化の指標の適用[Refereed]Scientific journal
- Sep. 2019, 第18回情報科学技術フォーラム (FIT-2019), 2, 69 - 72, Japaneseエージェントのタイプを用いた特性関数の簡略表記法に基づく制限付き提携構造形成問題[Refereed]Symposium
- Sep. 2019, Joint Agent Workshop and Symposium (JAWS-2019), accepted, JapaneseMC-netsによる利得分配問題の最小コアを求める複数制約生成法[Refereed]Symposium
- Jul. 2019, International Symposium on Scheduling 2019 (ISS 2019), 162 - 167, EnglishResilient Nurse Scheduling Problem[Refereed]Symposium
- Jun. 2019, 人工知能学会全国大会 (JSAI 2019), JapaneseU12バスケットボールにおけるリーグ戦スケジューリングResearch society
- Jun. 2019, The International Journal on Marine Navigation and Safety of Sea Transportation, 13, 117 - 124, EnglishDSSA+: Distributed Collision Avoidance Algorithm in an Environment where Both Course and Speed Changes are Allowed[Refereed]Scientific journal
- Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 495 - 496, Japanese分散最適化アルゴリズムによる自律編成型艦隊制御に関する一考察Research society
- Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 475 - 476, Japanese不確実性を考慮したタイプ付き提携構造形成アルゴリズムResearch society
- Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 493 - 494, Japanese速度制御を考慮に入れた分散衝突回避アルゴリズムResearch society
- Mar. 2019, 情報処理学会第81回全国大会, (1) (1), 329 - 330, Japaneseスポーツ・スケジューリング:ミニバスケットボールにおけるリーグ戦作成問題Research society
- Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 473 - 474, Japaneseエージェントのタイプに基づく制限付き提携構造形成問題Research society
- Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 471 - 472, JapaneseMC-netsにおける利得分配問題の最小コアを求める複数制約生成法Research society
- Mar. 2019, 情報処理学会第81回全国大会, (1) (1), 327 - 328, Japanese0-1整数計画法によるレジリエントなナース・スケジューリングResearch society
- 2019, Annals of Mathematics and Artificial Intelligence, 88(7) (7), 691 - 715, English[Refereed]Scientific journal
- Oct. 2018, In proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018), 663 - 664, EnglishProbabilistic Coalition Structure Generation[Refereed]International conference proceedings
- Oct. 2018, In proceedings of the 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2018), 123 - 139, EnglishBounded Approximate Algorithm for Probabilistic Coalition Structure Generation[Refereed]International conference proceedings
- Sep. 2018, 第 17 回情報科学技術フォーラム (FIT-2018), 37 - 40, Japaneseレジリエントなナース・スケジューリング問題[Refereed]Research society
- Sep. 2018, 第 17 回情報科学技術フォーラム (FIT-2018), 25 - 30, Japaneseエージェントのタイプに基づく確率的提携構造形成問題[Refereed]Research society
- Jun. 2018, 人工知能学会全国大会 (JSAI 2018), Japanese分散確率的探索アルゴリズムを用いた船舶衝突回避における非協力船舶の影響Research society
- Jun. 2018, 人工知能学会全国大会 (JSAI 2018), Japanese確率的な提携構造形成問題における精度保証付き近似解法の提案Research society
- Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 343 - 344, Japanese列生成法と LP ラウンディングによる提携構造形成アルゴリズムResearch society
- Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 351 - 352, Japanese時間拡張グラフ上のナンバーリンクパズルとしてのマルチエージェント経 路発見Research society
- Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 1, 335 - 336, Japanese公平性を考慮した麻酔科医スケジューリング問題に関する一検討Research society
- Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 375 - 376, Japanese共同研究チーム編成ツールの開発Research society
- Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 345 - 346, Japanese確率的な提携構造形成問題の解法Research society
- Blackwell Publishing Inc., Feb. 2018, Computational Intelligence, 34(1) (1), 49 - 84, English[Refereed]Scientific journal
- 2018, International Symposium on Artificial Intelligence and Mathematics, ISAIM 2018, Fort Lauderdale, Florida, USA, January 3-5, 2018.Stochastic Game Modelling for Distributed Constraint Reasoning with Privacy.[Refereed]International conference proceedings
- SciTePress, Jan. 2018, Proceedings of the 10th International Conference on Agents and Artificial Intelligence (ICAART-2018), 37 - 47, English[Refereed]International conference proceedings
- Jan. 2018, Proceedings of the 10th International Conference on Agents and Artificial Intelligence (ICAART-2018), 184 - 191, EnglishArea Protection in Adversarial Path-finding Scenarios with Multiple Mobile Agents on Graphs - A Theoretical and Experimental Study of Strategies for Defense Coordination[Refereed]International conference proceedings
- IOS Press, 2018, Fundamenta Informaticae, 158(1-3) (1-3), 63 - 91, English[Refereed]Scientific journal
- Sep. 2017, 第16回情報科学技術フォーラム(FIT-2017), 2, 65 - 70, Japanese確率的な提携構造形成フレームワークの提案[Refereed]Research society
- Jul. 2017, JOURNAL OF NAVIGATION, 70(4) (4), 699 - 718, English[Refereed]Scientific journal
- May 2017, 人工知能学会全国大会 (JSAI 2017), Japanese不確実性を考慮した提携構造形成問題に関する一検討Research society
- Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), 2, 355 - 356, Japanese乗合バス路線に基づく災害ロードマップ作成Research society
- Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), Japanese制約充足問題におけるインフルエンシャル変数の特定Research society
- Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), 2, 45 - 46, JapaneseMC-netsに基づく大規模提携形ゲームのための上界保証付きイプシロンコアResearch society
- Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), 2, 357 - 358, JapaneseDMAT編成問題Research society
- 2017, CoRR, abs/1703.06939Distributed Constraint Problems for Utilitarian Agents with Privacy Concerns, Recast as POMDPs.Scientific journal
- AAAI Press, 2017, Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference(FLAIRS), 454 - 459Utilitarian Approach to Privacy in Distributed Constraint Optimization Problems.International conference proceedings
- 2017, MULTI-AGENT AND COMPLEX SYSTEMS, 670, 139 - 152, English[Refereed]International conference proceedings
- Springer Singapore, Nov. 2016, Multi-agent and Complex Systems, 139 - 152, EnglishMulti-objective Nurse Rerostering Problem[Refereed]Scientific journal
- Jun. 2016, 第30回人工知能学会全国大会 (JSAI 2016), 2, 623 - 624, Japanese分散制約充足問題:大域的な決定に影響を及ぼすエージェントの特定に関する一検討Research society
- Jun. 2016, 第30回人工知能学会全国大会 (JSAI 2016), EnglishDistributed Stochastic Search Algorithm for n-Ship Collision AvoidanceResearch society
- Japanese Society for Artificial Intelligence, Feb. 2016, Transactions of the Japanese Society for Artificial Intelligence, 31(2) (2), Japanese[Refereed]Scientific journal
- Feb. 2016, 人工知能学会論文誌, 31(2) (2), pp.C - F75_1-10, Japanese分散ラグランジュ緩和プロトコルにおけるバンドル法[Refereed]Scientific journal
- AAAI Press, 2016, Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016, 98 - 103, EnglishBayesian network-based extension for PGP - Estimating petition supportInternational conference proceedings
- 2016, CoRR, abs/1604.06790DisCSPs with Privacy Recast as Planning Problems for Utility-based Agents.Scientific journal
- 2016, CoRR, abs/1604.06787Utilitarian Distributed Constraint Optimization Problems.Scientific journal
- Cépaduès Éditions, 2016, Systèmes Multi-Agents et simulation - Vingt-quatrièmes journées francophones sur les systèmes multi-agents(JFSMA), 129 - 138Privacité dans les DisCSP pour agents utilitaires.International conference proceedings
- 2016, 2016 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2016), 359 - 366, English[Refereed]International conference proceedings
- Jan. 2016, ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 15(1) (1), English[Refereed]Scientific journal
- Nov. 2015, The 16th International Symposium on Advanced Intelligent Systems (ISIS 2015), 781 - 793, EnglishSkill-Based Dynamic Team Formation Problem[Refereed]Symposium
- Nov. 2015, The 16th International Symposium on Advanced Intelligent Systems (ISIS 2015), 1100 - 1112, EnglishDistributed Stochastic Search Algorithm for n-Ship Collision Avoidance[Refereed]Symposium
- Oct. 2015, 合同エージェントワークショップ&シンポジウム (JAWS 2015), 16 - 17, Japanese増床計画付き患者搬送問題の定式化とヒューリスティック解法の提案Symposium
- Oct. 2015, 合同エージェントワークショップ&シンポジウム (JAWS 2015), 200 - 203, Japanese災害派遣医療チームのためのダイナミック・スケジューリング[Refereed]Symposium
- Jul. 2015, In proceedings of the International Symposium on Scheduling 2015 (ISS-15), 109 - 114, EnglishFavorable Solution in Multi-Objective Nurse Rerostering Problem[Refereed]Symposium
- Jun. 2015, 第29回人工知能学会全国大会 (JSAI 2015), English多目的ナース・リスケジューリング問題における平等性Research society
- 人工知能学会, Jun. 2015, 第29回人工知能学会全国大会 (JSAI-2015), 29, 1 - 4, EnglishEgalitarianism in Multi-Objective Nurse Rerostering ProblemResearch society
- 人工知能学会, May 2015, 第29回人工知能学会全国大会 (JSAI-2015), 29, 1 - 4, EnglishShip Collision Avoidance by Distributed Tabu SearchResearch society
- 人工知能学会, May 2015, 第29回人工知能学会全国大会 (JSAI-2015), 29, 1 - 4, JapaneseMax-SATに対する非厳密解法を用いたラグランジュ分解・調整法Research society
- 人工知能学会, Mar. 2015, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol.9(No.1) (No.1), 23 - 29, EnglishShip Collision Avoidance by Distributed Tabu Search[Refereed]Scientific journal
- Jan. 2015, The AAAI-15 Workshop on Planning, Search, and Optimization (PlanSOpt-15). In conjunction with AAAI-2015, 47 - 54, EnglishEffect of Bundle Method in Distributed Lagrangian Relaxation Protocol[Refereed]Symposium
- 2015, PRIMA 2015: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS, 9387, 134 - 151, English[Refereed]International conference proceedings
- Oct. 2014, 合同エージェントワークショップ&シンポジウム (JAWS-2014), 245 - 248, Japanese分散ラグランジュ緩和プロトコルにおけるバンドル法の効果[Refereed]Symposium
- Fuji Technology Press, Sep. 2014, Journal of Advanced Computational Intelligence and Intelligent Informatics, 18(5) (5), 839 - 848, EnglishCollision Avoidance in Multiple-Ship Situations by Distributed Local Search[Refereed]Scientific journal
- 人工知能学会, May 2014, 2014年度人工知能学会全国大会(第28回) (JSAI-2014) 講演論文集, 28, 1 - 4, Japaneseリンクの脆弱性を考慮したネットワーク連結性維持アルゴリズムResearch society
- IFAAMAS/ACM, 2014, International conference on Autonomous Agents and Multi-Agent Systems(AAMAS), 1569 - 1570Open census for addressing false identity attacks in agent-based decentralized social networks.International conference proceedings
- 2014, LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2122 - 2129, EnglishBilingual Dictionary Induction as an Optimization Problem[Refereed]International conference proceedings
- 2014, PRICAI 2014: TRENDS IN ARTIFICIAL INTELLIGENCE, 8862, 221 - 234, EnglishPivot-Based Bilingual Dictionary Extraction from Multiple Dictionary Resources[Refereed]International conference proceedings
- 2014, PRIMA 2014: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS, 8861, 423 - 438, EnglishLeximin Multiple Objective Optimization for Preferences of Agents[Refereed]International conference proceedings
- 2014, PRIMA 2014: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS, 8861, 319 - 332, EnglishComputing a Payoff Division in the Least Core for MC-nets Coalitional Games[Refereed]International conference proceedings
- 尾道市立大学経済情報学部, Dec. 2013, 尾道市立大学経済情報論集 = Journal of economics, management & information science, 13(2) (2), 167 - 181, Japanese[Refereed]
- 多層一般化相互割当問題の定式化とその解法<特集>ソフトウェアエージェントとその応用論文The Institute of Electronics, Information and Communication Engineers, Dec. 2013, 電子情報通信学会論文誌D, J96-D(12) (12), 2908 - 2919, Japanese[Refereed]Scientific journal
- Dec. 2013, Proceedings of the 16th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2013), EnglishEmbedding Preference Ordering for Single-phase Self-stabilizing DCOP Solvers[Refereed]International conference proceedings
- Nov. 2013, Proceedings of the 14th International Symposium on Advanced Intelligent Systems(ISIS 2013), EnglishShip Collision Avoidance using Distributed Local Search[Refereed]Scientific journal
- Aug. 2013, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013), 566 - 572, EnglishDeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP[Refereed]International conference proceedings
- 人工知能学会, Jun. 2013, 2013年度人工知能学会全国大会(第27回) (JSAI-2013) 講演論文集, 27, 1 - 4, Japanese列生成法を用いた提携形ゲームのコア非空性判定アルゴリズムResearch society
- Jun. 2013, 2013年度人工知能学会全国大会(第27回) (JSAI-2013) 講演論文集, JapaneseSATによる車両運用計画問題の定式化と集中/分散解法Research society
- Jun. 2013, 2013年度人工知能学会全国大会(第27回) (JSAI-2013) 講演論文集, JapaneseMulti-MaxSATにおけるバンドル法の効果Research society
- IEEE Computer Society, 2013, 2013 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 50 - 57International conference proceedings
- 2013, Transactions of the Japanese Society for Artificial Intelligence, 28(1) (1), 34 - 42, Japanese[Refereed]Scientific journal
- 2013, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8291, 197 - 212, English[Refereed]International conference proceedings
- 2013, 13TH IEEE INTERNATIONAL CONFERENCE ON PEER-TO-PEER COMPUTING (P2P), EnglishDirectDemocracyP2P-Decentralized Deliberative Petition Drives[Refereed]International conference proceedings
- 2013, Proceedings of the 12th International Conference on Autonomous Agents & Multi-agent Systems (AAMAS-2013), 1325 - 1326, EnglishDeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP (Extended Abstract)[Refereed]International conference proceedings
- 社団法人人工知能学会, Jan. 2013, Transactions of the Japanese Society for Artificial Intelligence, 28(1) (1), 34 - 42, Japanese値推移コスト付き動的制約充足問題とその解法[Refereed]Scientific journal
- 社団法人人工知能学会, 2013, Transactions of the Japanese Society for Artificial Intelligence, 28(1) (1), 43 - 56, Japanese[Refereed]Scientific journal
- 2013, 2013 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS), 72 - 77, EnglishLocation-dependent Content-based Image Retrieval System Based on a P2P Mobile Agent Framework[Refereed]International conference proceedings
- 一般社団法人情報処理学会, Nov. 2012, 情報処理学会論文誌, 53(11) (11), 2370 - 2378, JapaneseDistributed Lagrangian Relaxation Protocol for the Over-constrained Generalized Mutual Assignment Problem[Refereed]Scientific journal
- 2012, International Symposium on Artificial Intelligence and Mathematics(ISAIM)Soft Nonlinearity Constraints and their Lower-Arity Decomposition.International conference proceedings
- 2012, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7455, 137 - 152, English[Refereed]International conference proceedings
- 2012, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7514, 561 - 576, English[Refereed]International conference proceedings
- 2012, 2012 SEVENTH INTERNATIONAL CONFERENCE ON BROADBAND, WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS (BWCCA 2012), 82 - 87, English[Refereed]International conference proceedings
- We address a dynamic decision problem in which decision makers must pay some costs when they change their decisions along the way. We formalize this problem as Dynamic SAT (DynSAT) with decision change costs, whose goal is to find a sequence of models that minimize the aggregation of the costs for changing variables. We provide two solutions to solve a specific case of this problem. The first uses a Weighted Partial MaxSAT solver after we encode the entire problem as a Weighted Partial MaxSAT problem. The second solution, which we believe is novel, uses the Lagrangian decomposition technique that divides the entire problem into sub-problems, each of which can be separately solved by an exact Weighted Partial MaxSAT solver, and produces both lower and upper bounds on the optimal in an anytime manner. To compare the performance of these solvers, we experimented on the random problem and the target tracking problem. The experimental results show that a solver based on Lagrangian decomposition performs better for the random problem and competitively for the target tracking problem.The Japanese Society for Artificial Intelligence, Oct. 2011, 人工知能学会論文誌, Vol.26, No.6, pp.682-691(6) (6), 682 - 691, Japanese[Refereed]Scientific journal
- 2011, Transactions of the Japanese Society for Artificial Intelligence, 26(1) (1), 179 - 189, Japanese[Refereed]Scientific journal
- 2011, Transactions of the Japanese Society for Artificial Intelligence, 26(1) (1), 59 - 67, Japanese[Refereed]Scientific journal
- 2011, Transactions of the Japanese Society for Artificial Intelligence, 26(1) (1), 136 - 146, Japanese[Refereed]Scientific journal
- Jan. 2011, 人工知能学会論文誌, Vol.26, No.1, pp.179--189, Japanese分散制約最適化問題に基づく提携構造形成問題[Refereed]Scientific journal
- Jan. 2011, 人工知能学会論文誌, Vol.26, No.1, pp.59--67, Japanese分散ラグランジュ緩和プロトコルにおける適応的な価格更新[Refereed]Scientific journal
- 人工知能学会, Jan. 2011, 人工知能学会論文誌, Vol.26, No.1, pp.136--146, 1 - 4, Japanese敵対者に対応する協調問題解決:限量記号付き分散制約充足問題[Refereed]Scientific journal
- 2011, IJCAI International Joint Conference on Artificial Intelligence, pp.560--565, 560 - 565, English[Refereed]International conference proceedings
- 2011, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6876, 54 - 68, English[Refereed]International conference proceedings
- 2011, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6876, 576 - 590, English[Refereed]International conference proceedings
- 2011, AGENTS IN PRINCIPLE, AGENTS IN PRACTICE, 7047, 174 - 186, EnglishDistributed Lagrangian Relaxation Protocol for the Over-constrained Generalized Mutual Assignment Problem[Refereed]International conference proceedings
- May 2010, Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-2010), pp.1023–1030, 1023 - 1030, EnglishA Quantified Distributed Constraint Optimization Problem[Refereed]International conference proceedings
- Mar. 2010, 人工知能学会論文誌, Vol.25, No.3, pp.410-422, Japanese分散制約最適化問題へのソフトアーク整合の適用[Refereed]Scientific journal
- 2010, Transactions of the Japanese Society for Artificial Intelligence, 25(3) (3), 410 - 422, Japanese[Refereed]Scientific journal
- 2010, PROCEEDINGS OF THE TWENTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-10), pp.197--203, 197 - 203, EnglishCoalition Structure Generation Based on Distributed Constraint Optimization[Refereed]International conference proceedings
- Jul. 2009, 人工知能学会論文誌, Vol.24, No.5, pp.417-427, Japanese資源制約に束縛されないpseudo-treeを用いた資源制約付き分散制約最適化問題の解法[Refereed]Scientific journal
- May 2009, Proceedings of the 8th International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS-2009), pp.1065-1072, 1065 - 1072, EnglishDirected Soft Arc Consistency in Pseudo Trees[Refereed]International conference proceedings
- Japanese Society for Artificial Intelligence, 2009, Transactions of the Japanese Society for Artificial Intelligence, 24(5) (5), 417 - 427, Japanese[Refereed]Scientific journal
- Multi-MaxSAT: ラグランジュ分解・調整法を用いたWeighted Max-SATの解法Weighted Max-SAT問題とは, SAT問題における各節に重みを与え,満足できない節の重み和を最小にするような論理変数への真偽値の割当を求める最適化問題である. SAT問題に関する研究が近年劇的に進展したことを受けて, SAT問題の最適化版であるWeighted Max-SAT問題への関心も最近高まりつつある.本論文では,複数の部分問題(節集合)が互いに緩く結合することにより構成されるWeighted Max-SAT問題に対して特に有効な新しい解法としてMulti-MaxSATを提案する.評価実験によれば,部分問題間で共有される変数の数が比較的少ないとき, Multi-MaxSATは,最新の代表的な厳密解法や発見的解法よりも処理時間や発見できる解の質の面で優れている.The Institute of Electronics, Information and Communication Engineers, Jan. 2009, 電子情報通信学会論文誌D, Vol.J92-D, No.1, pp.51-60(1) (1), 51 - 60, Japanese[Refereed]Scientific journal
- AAAI Press, Jul. 2008, Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-2008), pp.120-125, 120 - 125, EnglishResource Constrained Distributed Constraint Optimization with Virtual Variables[Refereed]International conference proceedings
- IFAAMAS, May 2008, The Seventh International Conference on Autonomous Agents and Multi-agent Systems (AAMAS2008), 1(1) (1), 1405 - 1408, EnglishResource constrained distributed constraint optimization using resource constraint free pseudo-tree[Refereed]International conference proceedings
- Jul. 2007, Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-2007), pp.744-749, EnglishAn α-approximation Protocol for the Generalized Mutual Assignment Problem[Refereed]Scientific journal
- 2007, PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, EnglishDisLRP_alpha: alpha-approximation in Generalized Mutual AssignmentInternational conference proceedings
- 2007, Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, EnglishAn alpha-approximation Protocol for the Generalized Mutual Assignment ProblemInternational conference proceedings
- Jul. 2006, Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-2006), pp.660-665, EnglishA New Approach to Distributed Task Assignment using Lagrangian Decomposition and Distributed Constraint Satisfaction[Refereed]Scientific journal
- 2006, Proceedings of the International Conference on Autonomous Agents, 2006, 890 - 892, English[Refereed]International conference proceedings
- Distributed Lagrangean Relaxation Protocol for the Generalized Mutual Assignment Problem容量制約がある複数の機械(エージェント)に仕事(ジョブ)を適切に割り当てるという問題は, オペレーションズリサーチの分野では一般化割当問題として比較的古くから研究されている. 本研究では, この一般化割当問題を拡張し, 複数のエージェントが相互にジョブを適切に割り当てることを目指す一般化相互割当問題を導入する. また, それを解く分散型の解法である分散ラグランジュ緩和プロトコルを提案し, その性質を実験により明らかにする.The Institute of Electronics, Information and Communication Engineers, Sep. 2005, The IEICE Transactions on Information and Systems, PT.1 (Japanese Edition), Vol.J88-D-I, No.9, pp.1269-127(9) (9), 1269 - 1277, Japanese[Refereed]Scientific journal
- Jan. 2005, ARTIFICIAL INTELLIGENCE, 161(1-2) (1-2), 89 - 115, English[Refereed]Scientific journal
- Jan. 2005, ARTIFICIAL INTELLIGENCE, 161(1-2) (1-2), 229 - 245, English[Refereed]Scientific journal
- Sep. 2004, IPSJ Journal, Vol.45, No.9, pp.2217-2225, EnglishAn Easy-Hard-Easy Cost Profile in Distributed Constraint Satisfaction[Refereed]Scientific journal
- Mar. 2003, ARTIFICIAL INTELLIGENCE, 144(1-2) (1-2), 125 - 156, English[Refereed]Scientific journal
- Springer, Sep. 2002, Proceedings of the Eighth International Conference on Principles and Practice of Constraint Programming (CP-2002), pp.387--401, 387 - 401, English[Refereed]Scientific journal
- Jul. 2002, Proceedings of the First International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS-2002), pp.1199--1206, 1199 - 1206, EnglishLocal Search for Distributed SAT with Complex Local Problems[Refereed]Scientific journal
- Aug. 2001, Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI-2001), pp.1152-1158(1-2) (1-2), 125 - 156, English[Refereed]Scientific journal
- Jun. 2000, AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 3(2) (2), 185 - 207, EnglishAlgorithms for distributed constraint satisfaction: A review[Refereed]Scientific journal
- 制約充足テクニックを用いた移動体通信の周波数割当問題の解法This paper presents a new algorithm for solving frequency assignment problems in cellular mobile systems using constraint satisfaction techniques. The characteristics of this algorithm are as follows : 1) instead of representing each call in a cell (a unit area in providing communication services) as a variable, we represent a cell (which has multiple calls) as a variable that has a very large domain, and determine a variable value step by step, 2) a branch-and-bound search that incorporates forward-checking is performed, 3) a powerful cell-ordering heuristic is introduced, and 4) the limited discrepancy search is introduced to improve the chance of finding a solution in a limited amount of search. Experimental evaluations using standard benchmark problems show that this algorithm can find optimal or semi-optimal solutions for these problems, and most of the obtained solutions are better than or equivalent to those of existing methods using simulated annealing, tabu search, or neural networks. These results show that state-of-the-art constraint satisfaction / optimization techniques are capable of solving realistic application problems when equipped with an appropriate problem representation and heuristics.Information Processing Society of Japan (IPSJ), Apr. 2000, 情報処理学会論文誌, Vol.41,No.4, pp.1234-1243(4) (4), 1234 - 1243, Japanese[Refereed]Scientific journal
- Apr. 2000, Proceedings of the 20th IEEE International Conference on Distributed Computing Systems (ICDCS-2000), pp.169-177, 169 - 177, EnglishThe Effect of Nogood Learning in Distributed Constraint Satisfaction[Refereed]Scientific journal
- 分散制約充足におけるnogood学習の効果We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in the CSP literature and can efficiently make effective nogoods.We combine the method with the asynchronous weak-commitment search algorithm (AWC) and evaluate the performance of the resultant algorithm on distributed 3-coloring problems and distributed 3SAT problems. As a result, we found that the resolvent-based learning works well compared to previous learning methods for distributed constraint satisfaction algorithms. We also found that the AWC with the resolvent-based learning is able to find a solution with fewer cycles than the distributed breakout algorithm, which was known to be the most efficient algorithm (in terms of cycles) for solving distributed CSPs.人工知能学会, Mar. 2000, 人工知能学会誌, Vol.15, No.2, pp.355-361(2) (2), 355 - 361, Japanese[Refereed]Scientific journal
- 複雑な局所問題に対応する分散制約充足アルゴリズムA distributed constraint satisfaction problem can formalize various application problems in Multiagent systems, and several algorithms for solving this problem have been developed. One limitation of these algorithms is that they assume each agent has only one local variable. Although simple modifications enable these algorithms to handle multiple local variables, obtained algorithms are neither efficient nor scalable to larger problems.We develop a new algorithm that can handle multiple local variables efficiently, which is based on the asynchronous weak-commitment search algorithm. In this algorithm, a bad local solution can be modified without forcing other agents to exhaustively search local problems. Also, the number of interactions among agents can be decreased since agents communicate only when they find local solutions that satisfy all of the local constraints. Experimental evaluations show that this algorithm is far more efficient than an algorithm that uses the prioritization among agents.人工知能学会, Mar. 2000, 人工知能学会誌, Vol.15, No.2, pp.348-354(2) (2), 348 - 354, Japanese[Refereed]Scientific journal
- Springer, 2000, Principles and Practice of Constraint Programming - CP 2000(CP), 515 - 519International conference proceedings
- 2000, 2000 IEEE 51ST VEHICULAR TECHNOLOGY CONFERENCE, PROCEEDINGS, VOLS 1-3, pp.888--894, 888 - 894, EnglishFrequency assignment for cellular mobile systems using constraint satisfaction techniques[Refereed]International conference proceedings
- 2000, FOURTH INTERNATIONAL CONFERENCE ON MULTIAGENT SYSTEMS, PROCEEDINGS, pp.135-142, 135 - 142, EnglishAn approach to over-constrained distributed constraint satisfaction problems: Distributed hierarchical constraint satisfaction[Refereed]International conference proceedings
- Springer Verlag, 1999, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1713, 490 - 491, English[Refereed]International conference proceedings
- Jan. 1999, 人工知能学会誌, Vol.14, No.4, pp.636-645, Japanese分散不完全制約充足問題[Refereed]Scientific journal
- Jun. 1998, 情報処理学会論文誌, Vol.39, No.6, pp.1889-1897(6) (6), 1889 - 1897, Japanese分散breakout:反復改善型分散制約充足アルゴリズム[Refereed]Scientific journal
- 1998, INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS, PROCEEDINGS, pp.372-379, 372 - 379, EnglishDistributed constraint satisfaction algorithm for complex local problems[Refereed]International conference proceedings
- 1997, PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING - CP 97, 1330, 222 - 236, EnglishDistributed partial constraint satisfaction problem[Refereed]Scientific journal
- Dec. 1996, Proceedings of Second International Conference on Multiagent Systems (ICMAS-1996), pp.401-408, 401 - 408, EnglishDistributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems[Refereed]Scientific journal
- 分散制約充足におけるエージェントの非集中的組織化We have proposed LMO (Local Minimum driven Organizing) as a group forming mechanism for agents that solve Distributed Constraint Satisfaction problems. It is summarized as follows. When an agent (A1) gets caught in a local minimum, 1) A1 sends its local CSP to the agent (A2) that shares a violated constraint, 2) A2 puts their CSP together and searches for all possible assignments with simple backtracking. One flaw of LMO is that the cost of search grows exponentially with the number of CSP being put together. To cope with this flaw we extend our method as follows and introduce the dynamically weight adjusting strategy : ・ We associate a weight with each constraint. The weights have 1 as their initial values ; ・ We measure the cost of instantiation as the sum of weights of violated constraints ; ・ Strategy : after putting CSP together, A2 sends neighbors the number of variables or the size of domain ; neighbors reassign it for the weights of constraints being shared with A2. The result of the experiment on distributed 3-coloring problem was that this strategy tended to protect against concentration of CSP and reduced the cost of search.Jul. 1995, 人工知能学会誌, Vol.10, No.4, pp.636-640(4) (4), 636 - 640, Japanese[Refereed]Scientific journal
- Jun. 1995, Proceedings of First International Conference on Multiagent Systems (ICMAS-1995), pp.155-162, 155 - 162, EnglishForming Coalitions for Breaking Deadlocks[Refereed]Scientific journal
- 山登り法を用いた分散制約充足における組織化DCSP (Distributed Constraint Satisfaction Problem) provides a formal framework for studying cooperative distributed problem solving. Several algorithms for DCSP have been proposed. This paper presents a new method, LMO (Local Minimum driven Organizing), to solve DCSP. The basic algorithm is iterative improvement. Each agent measures the cost of its own instantiations as the number of violated constraints. If local change of instantiations reduces the cost, the agent performs hill-climbing locally. The advantage of this method is that agents solve their local problems in Parallel. 0ne drawback, however, is the possibility of getting caught in local minima. LMO provides a technique for escaping from local minima. It is summarized as follows. When an agent (A1) gets caught in a local minimum, 1) A1 sends its local CSP to the agent (A2) that shares a violated constraint with it, 2) A2 puts their CSPs together and solve them by a brute-force search.It eliminates local minima from search spaces, alters a hill-climbing for a brute-force search, and reduces communication overhead at the cost of the parallel execution. It is triggered by a local minimum, therefore the more local minima agents get caught, the more CSPs are put together and solved with a brute-force search. This means that the algorithm is adaptable to the problem it solves. In this paper, we verify this fact experimentally.Jan. 1995, 人工知能学会誌, Vol.10, No.1, pp.80-87(1) (1), 80 - 87, Japanese[Refereed]Scientific journal
- 人工知能学会, May 2013, 人工知能学会誌, 28(3) (3), 380 - 388, Japanese制約充足や最適化に関するエージェント研究の最近の動向[Refereed]Introduction scientific journal
- Mar. 2013, コンピュータソフトウェア, 30(1):16-19, Japanese国際シンポジウムFLOPS 2012開催報告[Refereed]Others
- Mar. 2013, コンピュータソフトウエア, 30(1) (1), 16 - 19, Japanese国際シンポジウムFLOPS2012開催報告[Refereed]Meeting report
- 人工知能学会, 2013, 人工知能学会全国大会論文集, 27, 1 - 4, JapaneseCentralized and Distributed SAT for the Rolling Stock Operation Problem
- 01 Nov. 2012, 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence, 27(6) (6), 650 - 650, JapaneseOS-04 SAT技術の理論,実装,応用(オーガナイズドセッション報告,<特集>2012年度人工知能学会全国大会(第26回))
- 人工知能学会, 02 Feb. 2012, 人工知能基本問題研究会, 85, 19 - 21, JapaneseDistributed Optimization Problems and Their Solutions for Multi-Agent Systems
- 人工知能学会, 2012, 人工知能学会全国大会論文集, 26, 1 - 4, JapaneseAsynchronous Backtracking Algorithms for Clause-set Partitioned Distributed SAT
- 人工知能学会, 2012, 人工知能学会全国大会論文集, 26, 1 - 4, JapaneseDeQED : DCOP Solving by Exchanging Dual Variables
- 人工知能学会, 2011, 人工知能学会全国大会論文集, 25, 1 - 4, JapaneseDynamic CSP with Decision Change Costs : Formalization and Solutions
- 人工知能学会, 01 Jan. 2010, Journal of Japanese Society for Artificial Intelligence, 25(1) (1), 105 - 113, Japanese*-SAT: Extentions of SAT(
Recent Advances in SAT Techniques) - Jan. 2010, 人工知能学会誌, Vol.25, No.1, pp.105-113, Japanese*-SAT: SATの拡張Introduction scientific journal
- 人工知能学会, 04 Dec. 2004, 知識ベ-スシステム研究会, 67, 73 - 78, EnglishDistributed Lagrangean Relaxation Protocol for the Generalized Mutual Assignment Problem (Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ and IEICE-SIGAI on Active Mining) -- (Session 3: Artificial Intelligence)
- 人工知能学会, 01 Mar. 2004, 知識ベ-スシステム研究会, 64, 183 - 188, JapaneseポアソンSAT過程における節の脆弱度と期待寿命 (特集 「医療及び化学情報マイニング」および一般)
- Distributed Task Assignment for Information GatheringThis paper describes a method to solve the distributed task assignment problem on a simple model of multi-agent information gathering. This model consists of two types of agents : Information Integration agents (I-agents) and Information Gathering agents (G-agents). I-agents assign tasks of watching some information sources to G-agents and G-agents notify I-agents of renewal of information sources that they have been watching. In this model, I-agents need to assign watching tasks so that the assignment meets not only users' requirements but also resource constraints imposed upon G-agents. Also, it is desirable that I-agents can obtain such an assignment without revealing users' requirements each other because such requirements may include some private information. In this paper, we encode this assignment problem as distributed SAT and solve it using a general-purpose distributed SAT algorithm.Information Processing Society of Japan (IPSJ), 13 Mar. 2003, IPSJ SIG Notes. ICS, 2003(30) (30), 63 - 68, Japanese
- Distributed Task Assignment for Information GatheringThis paper describes a method to solve the distributed task assignment problem on a simple model of multi-agent information gathering. This model consists of two types of agents: Information Integration agents (I-agents) and Information Gathering agents (G-agents). I-agents assign tasks of watching some information sources to G-agents and G-agents notify I-agents of renewal of information sources that they have been watching. In this model, I-agents need to assign watching tasks so that the assignment meets not only users' requirements but also resource constraints imposed upon G-agents. Also, it is desirable that I-agents can obtain such an assignment without revealing users' requirements each other because such requirements may include some private information. In this paper, we encode this assignment problem as distributed SAT and solve it using a general-purpose distributed SAT algorithm.The Institute of Electronics, Information and Communication Engineers, 07 Mar. 2003, IEICE technical report. Artificial intelligence and knowledge-based processing, 102(710) (710), 11 - 16, Japanese
- Dynamic Distributed Constraint Satisfaction Protocol for Active Information IntegrationWe present a dynamic distributed constraint satisfaction protocol that can be used to resolve conflicts among agents of the Intelligent Ticker System, which can gather and integrate various information on the Web. This paper briefly describes the overall system, identifies a conflict resolution problem in the system, shows how to map the problem into a dynamic distributed constraint satisfaction problem, and presents a general protocol for the dynamic distributed constraint satisfaction problem.Information Processing Society of Japan (IPSJ), 23 May 2002, IPSJ SIG Notes. ICS, 2002(45) (45), 175 - 180, Japanese
- 24 Jun. 1997, 人工知能学会全国大会論文集 = Proceedings of the Annual Conference of JSAI, 11, 449 - 451, JapaneseDevelopment of Environmental Definition Watcher System
- 人工知能学会, May 1997, 人工知能学会誌, Vol.12, No.3, pp.381-389(3) (3), 381 - 389, JapaneseCSPの新しい展開:分散/動的/不完全CSPIntroduction scientific journal
- 一般社団法人情報処理学会, 15 Sep. 1995, 情報処理, 36(9) (9), 893 - 895, JapaneseICMAS'95報告
- 20 Jun. 1994, 人工知能学会全国大会論文集 = Proceedings of the Annual Conference of JSAI, 8, 249 - 252, JapaneseBalancing an Organizing Load in Distributed Constraint Satisfaction
- 描画用制約プログラミング言語 : CLDの設計図形の描画という処理を、(1)描画対象の位置関係の認識(2)描画に必要なパラメータの計算(3)描画という具合に大きく3つに分けた場合、従来の図形描画用の計算機言語では、(1)と(2)を人間が担当し、(3)を計算機がやっていたといえる。本研究では、制約プログラミングの考え方を図形の描画に応用し、人間が(1)のみを行うことによって、図形を描画することができる描画用制約プログラミング言語CLD(Constraint programing Language for Drawing)及びそのインタプリタの設計を行う。04 Sep. 1990, 全国大会講演論文集, 41, 51 - 52, Japanese
- 9th International Conference on Advanced Intelligent Maritime Safety and Technology (Ai-MAST 2023), Nov. 2023, EnglishDistributed Ship Collision Avoidance Algorithms[Invited]Keynote oral presentation
- 2023年度人工知能学会全国大会(第37回) (JSAI-2023),OS-9「AIと制約プログラミング」招待講演, Jun. 2023, Japanese分散船舶衝突回避アルゴリズム[Invited]Invited oral presentation
- 5th Symposium on Multi Agent Systems for Harmonization 2022(SMASH22 Winter Symposium), Feb. 2022, Japanese深層強化学習による最適な分散衝突回避Oral presentation
- 第17回科学技術フォーラム (FIT-2018), Sep. 2018, Japanese, Domestic conferenceレジリエントなナース・スケジューリング問題Oral presentation
- 第17回科学技術フォーラム (FIT-2018), Sep. 2018, Japanese, Domestic conferenceエージェントのタイプに基づく確率的提携構造形成問題Oral presentation
- 人工知能学会全国大会 (JSAI 2018), Jun. 2018, Japanese, Domestic conference分散確率的探索アルゴリズムを用いた船舶衝突回避における非協力船舶の影響Oral presentation
- 人工知能学会全国大会 (JSAI 2018), Jun. 2018, Japanese, Domestic conference確率的な提携構造形成問題における精度保証付き近似解法の提案Oral presentation
- 情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference列生成法とLP ラウンディングによる提携構造形成アルゴリズムOral presentation
- 情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference時間拡張グラフ上のナンバーリンクパズルとしてのマルチエージェント経路発見Oral presentation
- 情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference公平性を考慮した麻酔科医スケジューリング問題に関する一検討Oral presentation
- 情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference共同研究チーム編成ツールの開発Oral presentation
- 情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference確率的な提携構造形成問題の解法Oral presentation
- 合同エージェントワークショップ & シンポジウム2017 (JAWS-2017), Sep. 2017, Japanese, 千葉県, Domestic conferenceMC-netsにおける利得分配:上界保証付きε-コアを求めるアルゴリズムOral presentation
- 日本ソフトウェア科学会第34回大会(2017年度)講演論文集, Sep. 2017, Japanese, 横浜, Domestic conferenceMC-netsにおける利得分配:上界保証付きε-コアを求めるアルゴリズムOral presentation
- 情報処理学会第79回全国大会 (IPSJ 2017), Mar. 2017, Japanese, Domestic conference乗合バス路線に基づく災害ロードマップ作成Oral presentation
- 情報処理学会第79回全国大会 (IPSJ 2017), Mar. 2017, Japanese, Domestic conferenceMC-netsに基づく大規模提携形ゲームのための上界保証付きイプシロンコアOral presentation
- 情報処理学会第79回全国大会 (IPSJ 2017), Mar. 2017, Japanese, Domestic conferenceDMAT編成問題Oral presentation
- 2016年度人工知能学会全国大会(第30回) (JSAI-2016), Jun. 2016, Japanese, Domestic conference分散制約充足問題:大域的な決定に影響を及ぼすエージェントの特定に関する一検討Oral presentation
- 2016年度人工知能学会全国大会(第30回) (JSAI-2016), Jun. 2016, English, 北九州, Domestic conferenceDistributed Stochastic Search Algorithm for n-Ship Collision AvoidanceOral presentation
- The 16th International Symposium on Advanced Intelligent Systems (ISIS-2015), Nov. 2015, English, Mokpo, Korea, International conferenceDistributed Stochastic Search Algorithm for n-Ship Collision AvoidancePoster presentation
- International Joint Agents Workshop and Symposium (IJAWS-2015), Oct. 2015, English, Kaga, Japan., International conferenceMulti-Objective Nurse Rerostering ProblemOral presentation
- 2015年度人工知能学会全国大会(第29回) (JSAI-2015), May 2015, Japanese, 函館, Domestic conference多目的ナース・リスケジューリング問題における平等性Oral presentation
- 2015年度人工知能学会全国大会(第29回), May 2015, English, 函館, Domestic conferenceShip Collision Avoidance by Distributed Tabu SearchOral presentation
- Proceedings of the 13th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2014), Dec. 2014, English, Gold Coast, Australia, International conferencePivot-based Bilingual Dictionary Extraction from Multiple Dictionary ResourcesOral presentation
- Proceedings of the 17th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2014), Dec. 2014, English, Gold Coast, Australia, International conferenceLeximin Multiple Objective Optimization for Preferences of AgentsOral presentation
- Proceedings of the 17th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2014), Dec. 2014, English, Gold Coast, Australia, International conferenceComputing a Payoff Division in the Least Core for MC-nets Coalitional GamesOral presentation
- 2014年度人工知能学会全国大会(第28回) (JSAI-2014), May 2014, Japanese, 松山, Domestic conferenceリンクの脆弱性を考慮したネットワーク連結性維持アルゴリズムOral presentation
- Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), May 2014, English, Reykjavik, Iceland, International conferenceBilingual Dictionary Induction as an Optimization ProblemOral presentation
- Proceedings of the 16th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2013), Dec. 2013, English, Dunedin, New Zealand, International conferenceEmbedding Preference Ordering for Symmetric DCOP Solvers on Spanning TreesOral presentation
- Proceedings of the 14th International Symposium on Advanced Intelligent Systems, Nov. 2013, English, Daejeon, Korea, International conferenceShip Collision Avoidance using Distributed Local SearchPublic symposium
- Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013), Aug. 2013, English, Beijing, China, International conferenceDeQED: an Efficient Divide-and-Coordinate Algorithm for DCOPOral presentation
- 2013年度人工知能学会全国大会(第27回), Jun. 2013, Japanese, 富山, Domestic conference列生成法を用いた提携形ゲームのコア非空性判定アルゴリズムOral presentation
- 2013年度人工知能学会全国大会(第27回), Jun. 2013, Japanese, 富山, Domestic conferenceSATによる車両運用計画問題の定式化と集中/分散解法Oral presentation
- 2013年度人工知能学会全国大会(第27回), Jun. 2013, Japanese, 富山, Domestic conferenceMulti-MaxSATにおけるバンドル法の効果Oral presentation
- 合同エージェントワークショップ & シンポジウム2012, Oct. 2012, Japanese, 掛川, Domestic conference多層一般化相互割当問題の定式化とその解法Oral presentation
- 合同エージェントワークショップ & シンポジウム2012, Oct. 2012, Japanese, 掛川, Domestic conferenceDeQED: 複雑な局所問題を伴う分散制約最適化問題のためのアルゴリズムOral presentation
- 2012年度人工知能学会全国大会(第26回), Jun. 2012, Japanese, 山口, Domestic conference節集合分割型分散SATに対する非同期バックトラッキングアルゴリズムOral presentation
- 2012年度人工知能学会全国大会(第26回), Jun. 2012, Japanese, 山口, Domestic conferenceDeQED: 双対変数の値を交換する分散制約最適化アルゴリズムOral presentation
- 人工知能基本問題研究会(第85回), Feb. 2012, Japanese, 下呂, Domestic conferenceマルチエージェントシステムにおける分散最適化問題とその解法Invited oral presentation
- Proceedings of the 11th International Workshop on Symmetry in Constraint Satisfaction Problems (SymCon-11), Sep. 2011, English, Perugia, Italy, International conferenceSymmetry of Nonlinearity ConstraintsOral presentation
- Proceedings of the 11th Workshop on Preferences and Soft Constraints (SofT-11), Sep. 2011, English, Perugia, Italy, International conferenceSoft Nonlinearity Constraints and their Lower-Arity DecompositionOral presentation
- 2011年度人工知能学会全国大会(第25回) (JSAI-2011), Jun. 2011, Japanese, 盛岡, Domestic conference複数供給源からの分散協調型エネルギー供給量決定プロトコルOral presentation
- 2011年度人工知能学会全国大会(第25回) (JSAI-2011), Jun. 2011, Japanese, 盛岡, Domestic conference値変更コスト付き動的CSPの定式化とその解法Oral presentation
- 合同エージェントワークショップ & シンポジウム2010 (JAWS-2010), Oct. 2010, Japanese, 富良野, Domestic conference値変更コスト付き動的SATのためのモデル追跡Oral presentation
- 合同エージェントワークショップ & シンポジウム2010 (JAWS-2010), Oct. 2010, Japanese, 富良野, Domestic conference過制約な一般化相互割当問題に対する分散ラグランジュ緩和プロトコルOral presentation
- Proceedings of the 10th Workshop on Preferences and Soft Constraints (SofT-10), Sep. 2010, English, St.Andrews, Scotland, International conferenceModel Tracking for Dynamic SAT with Decision Change CostsOral presentation
- 合同エージェントワークショップ & シンポジウム2008 (JAWS-2008), Oct. 2008, Japanese, 大津, Domestic conference分散ラグランジュ緩和プロトコルにおける適応的な価格更新Oral presentation
- 合同エージェントワークショップ & シンポジウム2007 (JAWS-2007), Oct. 2007, Japanese, 那覇, Domestic conference電子市場への財配分戦略:2+1市場複占モデルに対するサブゲーム完全な結果Oral presentation
- 合同エージェントワークショップ & シンポジウム2007 (JAWS-2007), Oct. 2007, Japanese, 那覇, Domestic conferenceMulti-MaxSAT: ラグランジュ分解・調整法を用いたMax-SATの解法Oral presentation
- Seventh International Workshop on Distributed Constraint Reasoning, May 2006, English, Hakodate, International conferenceA Distributed Solution Protocol that Computes an Upper Bound for the Generalized Mutual Assignment ProblemOral presentation
- Joint Agent Workshops & Symposium 2005, Nov. 2005, Japanese, 知能と複雑系研究会(情報処理学会), マルチエージェントと協調計算研究会(日本ソフトウエア科学会), 人工知能と知識処理研究会(電子情報通信学会), 知識ベースシステム研究会(人工知能学会), Hakone, Domestic conferenceA Distributed Lagrangean Relaxation Protocol that Computes a Upper BoundOral presentation
- Joint Agent Workshops & Symposium 2005, Nov. 2005, Japanese, 知能と複雑系研究会(情報処理学会), マルチエージェントと協調計算研究会(日本ソフトウエア科学会), 人工知能と知識処理研究会(電子情報通信学会), 知識ベースシステム研究会(人工知能学会), Hakone, Domestic conferenceRealtime Dynamic Constraint Satisfaction Problem: formalization and solving methodOral presentation
- First International Workshop on Distributed and Speculative Constraint Processing, Oct. 2005, English, Sitges, Spain, International conferenceDistributed Lagrangean Relaxation Protocol for the Generalized Mutual Assignment ProblemOral presentation
- 人工知能学会知識ベースシステム研究会(第64回)資料 SIG-KBS-A304 pp.183-188, Mar. 2004, Japanese, 人工知能学会 知識ベースシステム研究会, 九州大学, Domestic conferenceポアソンSAT過程における節の脆弱度と期待寿命Oral presentation
■ Research Themes
- 日本学術振興会, 科学研究費助成事業, 基盤研究(B), 神戸大学, 01 Apr. 2022 - 31 Mar. 2025全体最適と個人最適を両立させる分散協調問題解決
- 科学研究費補助金/基盤研究(B), Apr. 2017 - Mar. 2021Competitive research funding
- 学術研究助成基金助成金/基盤研究(C), Apr. 2017 - Mar. 2020, Principal investigatorCompetitive research funding
- 科学研究費補助金/基盤研究(B), Apr. 2017 - Mar. 2020Competitive research funding
- Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (S), Kyushu University, 31 May 2012 - 31 Mar. 2017Establishing Theory of Resource Allocation Mechanism Design for Sustainable DevelopmentHow to allocate precious resources becomes critical due to various pressing social issues, including energy, environmental, and aging population issues. The goal of this project is developing the theory of resource allocation mechanism design, which aims to make desirable decisions considering economic, social, and environmental needs when multiple agents exist, by synthesizing/extending technologies from computer science and micro economics. More specifically, we developed design, analytic, and representation technologies for resource allocation. In particular, we made notable contributions on mechanism design for constrained two-sided matching, equilibrium analysis for repeated games in noisy environments, and concise and efficient representations for coalitional games. The summary of publications of this project is as follows: refereed international conferences 87, international journals 74, domestic journals 11, research monographs 8, textbooks 4, invited talks 40.
- Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Nagoya Institute of Technology, 2009 - 2011Next Generation P2P video streaming system with high quality and low power.We propose the formalization and distributed cooperation methods for d-MST problem in multi-agent systems. The proposed exact/approximate methods resemble the approaches that apply Distributed Constraint Optimization Problem. In the exact method, each agent propagates messages that represent set of sub-trees in a bottom-up manner. We experimentally compare the proposed techniques from the viewpoints of the quality of the solutions and the cost for tree construction.
- 科学研究費補助金/基盤研究(B), 2011, Principal investigatorCompetitive research funding
- 特別研究員奨励費, 2011, Principal investigatorCompetitive research funding
- 科学研究費補助金/基盤研究(B), 2010Competitive research funding
- 科学研究費補助金/基盤研究(A), 2008Competitive research funding
- 科学研究費補助金/基盤研究(B), 2007, Principal investigatorCompetitive research funding
- 科学研究費補助金/基盤研究(C), 2005Competitive research funding
- 日本学術振興会, 科学研究費助成事業, 特定領域研究, 2001 - 2004分散動的情報源からのアクティブ情報収集1.分散動的情報源からの情報収集を指向した一般化相互割当プロトコル 2.発見ルールフィルタリングシステムの実装 発見ルールフィルタリングシステムDRFSを実装した.DRFSはミクロビューとマクロビューアプローチに基づく,ルールフィルタリングが可能である.ミクロビューアプローチでは文献の検索だけでなく,その経年変化を表示することができる.マクロビューアプローチではキーワードの関係をグラフを用いて視覚的に表現することができる.また新たなルールの登録機能も付加されている.これにより,肝炎データマイニングへの応用として新たに,計画研究A01-04(沼尾)との連携を行い,発見ルールの登録を行った.一方,Medlineからの文献検索に関してはまだ精度が十分でないので,計画研究A02-08(松本)との連携により,自然言語処理手法を用いた性能改善を行った.
- Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), KOBE UNIVERSITY OF MERCANTILE MARINE, 1998 - 2000Character and Line Figure Recognition in an ImageThe main purpose of this research is to develop a character and a line figure extraction methods applicable to various category of images. As character extraction methods, we have developed a character strings extraction method from magazine cover images and a telop extraction method from news video. The former is based on segmentation by the differential Top-hat operation, and we made effort to establishing the threshold by local histogram method and resolution of the competition between extracted character regions. The latter that is based on the morphological operation realized the detection of the telop frames and extraction the telop regions. For the line figure extraction, we have proposed a detection method of cracks and structural objects of the road surface image. An advantage of the method is its robustness against noise and vagueness of the objects. We have also made study on the parallel computing of the morphology operations and on the distributed constraint satisfaction.