Research activity information

• 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

  郷原 一眞, 平山 勝敏, 沖本 天太, キム ドンギュン


• 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

  宮家 昂希, 平山 勝敏, 沖本 天太, 塩田 知宏


• 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

  沖本 天太, 上田 俊, 平山 勝敏, 藤本 真育, 豊島 大弥


• 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 Generation

  Kouki Matsumura, Tenda Okimoto, Katsutoshi Hirayama


• 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

  HIRAYAMA KATSUTOSHI


• May 2010 International Foundation for Autonomous Agents and Multiagent Systems, IFAAMAS 2010 Influential Paper Award, Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems

  HIRAYAMA Katsutoshi

• Waterway traffic situation awareness based on multi-modal data fusion of smart buoys

  Xingchen Ji, Ruolan Zhang, Katsutoshi Hirayama

  Oct. 2024, Proceedings of Asia Navigation Conference 2024 (ANC-2024), 254 - 264


• ロバストな警備員配置問題

  沖本 天太, 鳴海 航, 平山 勝敏

  Mar. 2024, 情報処理学会第86回全国大会講演論文集


• U12 Basketball League Scheduling Problem Based on Minimizing the Total Traveling Distance and the Number of Breaks

  Tenda Okimoto, Katsutoshi Hirayama

  Japanese Society for Artificial Intelligence, Nov. 2023, Transactions of the Japanese Society for Artificial Intelligence, 38(6) (6), A - N31_1

  Link to Kobe Univ. Repository (Kernel)


• 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

  沖本天太, 平山勝敏

  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


• Ship Anomalous Behavior Detection Using Clustering and Deep Recurrent Neural Network

  Bohan Zhang, Katsutoshi Hirayama, Hongxiang Ren, Delong Wang, Haijiang Li

  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

  Link to Kobe Univ. Repository (Kernel)


• 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

  里山 大河, 平山 勝敏, 沖本 天太

  Mar. 2023, 情報処理学会第85回全国大会講演論文集


• Bounded Approximate Payoff Division for MC-nets Games

  Katsutoshi HIRAYAMA, Tenda OKIMOTO

  Institute of Electronics, Information and Communications Engineers (IEICE), Dec. 2022, IEICE Transactions on Information and Systems, E105.D(12) (12), 2085 - 2091

  Link to Kobe Univ. Repository (Kernel)


• 深層強化学習による最適な分散衝突回避

  郷原 一眞, 平山 勝敏, 沖本 天太, 金 東均

  Sep. 2022, 第21回情報科学技術フォーラム（FIT-2022）講演論文集


• 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

  東山 敏也, 平山 勝敏, 沖本 天太

  Sep. 2022, 第21回情報科学技術フォーラム（FIT-2022）講演論文集


• 回収と配達の両方に時間枠をもつMAPD

  渡邉 伸二, 平山 勝敏, 沖本 天太

  Sep. 2022, 第21回情報科学技術フォーラム（FIT-2022）講演論文集


• Influential Variables in Constraint Networks

  Li Qiancheng, 沖本 天太, 平山 勝敏

  Sep. 2022, 第21回情報科学技術フォーラム（FIT-2022）講演論文集


• Many-Objective Container Stowage Optimization Based on Improved NSGA-III

  Yuchuang Wang, Guoyou Shi, Katsutoshi Hirayama

  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


• Vessel Scheduling Optimization Model Based on Variable Speed in a Seaport with One-Way Navigation Channel

  Dongdong Liu, Guoyou Shi, Katsutoshi Hirayama

  Aug. 2021, Sensors, 21(16) (16)


• On the computation of probabilistic coalition structures

  Nicolas Schwind, Tenda Okimoto, Katsumi Inoue, Katsutoshi Hirayama, Jean-Marie Lagniez, Pierre Marquis

  Springer Science and Business Media LLC, Apr. 2021, Autonomous Agents and Multi-Agent Systems, 35(1) (1)


• 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

  加藤 浩晃, 沖本 天太, 平山 勝敏

  Dec. 2020, 電子情報通信学会論文誌, Vol.J103-D(No.12) (No.12), 853 - 859


• 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―

  寺村倖輔, 平山 勝敏, 沖本天太, 秋田直也

  Sep. 2020, 第19回情報科学技術フォーラム（FIT-2020）講演論文集


• Privacy Stochastic Games in Distributed Constraint Reasoning

  Julien Savaux, Julien Vion, Sylvain Piechowiak, Rene Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi

  Jul. 2020, Annals of Mathematics and Artificial Intelligence, 88(7) (7), 691 - 715


• 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

  井上 隆太, 沖本 天太, 平山 勝敏

  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

  塩田 知広, 平山 勝敏, 沖本 天太

  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

  原田 拓歩, 平山 勝敏, 沖本 天太, 國師 大朗

  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


• Two Approximation Algorithms for Probabilistic Coalition Structure Generation with Quality Bound

  Kouki Matsumura, Bojana Kodric, Tenda Okimoto, Katsutoshi Hirayama

  Apr. 2020, Autonomous Agent Multi-Agent Systems, 34(1) (1)

  Link to Kobe Univ. Repository (Kernel)


• 提携値の上下界を利用する提携構造形成アルゴリズム

  川元 沙恵, 平山 勝敏, 沖本 天太

  Mar. 2020, 情報処理学会第82回全国大会講演論文集


• 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

  沖本 天太, 上田 俊, 平山 勝敏

  Feb. 2020, 電子情報通信学会和文論文誌D, J103-D(2) (2), 42 - 51


• Identifying Influential Variables in CSP

  Tenda Okimoto, Katsutoshi Hirayama

  Dec. 2019, Proceedings of the 20th International Symposium on Advanced Intelligent Systems (ISIS 2019)


• 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

  松井俊浩, Marius C. Silaghi, 平山勝敏, 横尾真, 松尾啓志

  Oct. 2019, 情報処理学会論文誌, 60(10) (10), 1603 - 1616


• 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

  加藤 浩晃, 沖本 天太, 平山 勝敏

  Sep. 2019, 第18回情報科学技術フォーラム (FIT-2019), 2, 69 - 72


• MC-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

  小浦 隆之, 平山 勝敏, 沖本 天太

  Sep. 2019, Joint Agent Workshop and Symposium (JAWS-2019), accepted


• Resilient Nurse Scheduling Problem

  Motoki Yoshida, Tenda Okimoto, Katsutoshi Hirayama

  Jul. 2019, International Symposium on Scheduling 2019 (ISS 2019), 162 - 167


• U12バスケットボールにおけるリーグ戦スケジューリング

  沖本 天太, 西村 一輝, 平山 勝敏

  Jun. 2019, 人工知能学会全国大会 (JSAI 2019)


• DSSA+: Distributed Collision Avoidance Algorithm in an Environment where Both Course and Speed Changes are Allowed

  Katsutoshi Hirayama, Koki Miyake, Tomohiro Shiota, Tenda Okimoto

  Jun. 2019, The International Journal on Marine Navigation and Safety of Sea Transportation, 13, 117 - 124


• 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

  塩田 知広, 宮家 昂希, 平山 勝敏, 沖本 天太

  Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 495 - 496


• 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

  藤本 真育, 沖本 天太, 平山 勝敏

  Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 475 - 476


• 速度制御を考慮に入れた分散衝突回避アルゴリズム

  宮家 昂希, 平山 勝敏, 塩田 知広, 沖本 天太

  Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 493 - 494


• 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

  西村 一輝, 沖本 天太, 平山 勝敏

  Mar. 2019, 情報処理学会第81回全国大会, (1) (1), 329 - 330


• 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

  加藤 浩晃, 沖本 天太, 平山 勝敏

  Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 473 - 474


• MC-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

  小浦 隆之, 平山 勝敏, 沖本 天太

  Mar. 2019, 情報処理学会第81回全国大会, (2) (2), 471 - 472


• 0-1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

  吉田 基輝, 沖本 天太, 平山 勝敏

  Mar. 2019, 情報処理学会第81回全国大会, (1) (1), 327 - 328


• Privacy Stochastic Games in Distributed Constraint Reasoning

  Julien Savaux, Julien Vion, Sylvain Piechowiak, Rene Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi

  2019, Annals of Mathematics and Artificial Intelligence, 88(7) (7), 691 - 715


• Probabilistic Coalition Structure Generation

  Nicolas Schwind, Tenda Okimoto, Katsutoshi Hirayama, Katsumi Inoue, Jean-Marie Lagniez, Pierre Marquis

  Oct. 2018, In proceedings of the 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018), 663 - 664


• Bounded Approximate Algorithm for Probabilistic Coalition Structure Generation

  Kouki Matsumura, Tenda Okimoto, Katsutoshi Hirayama

  Oct. 2018, In proceedings of the 21st International Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2018), 123 - 139


• レジリエントなナース・スケジューリング問題

  沖本 天太, 平山 勝敏, 番原 睦則, 井上 克巳

  Sep. 2018, 第 17 回情報科学技術フォーラム (FIT-2018), 37 - 40


• 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

  沖本 天太, 上田 俊, 平山 勝敏, 藤本 真育, 豊島 大弥

  Sep. 2018, 第 17 回情報科学技術フォーラム (FIT-2018), 25 - 30


• 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

  唐渡 裕基, 平山 勝敏, 沖本 天太, 金 東均

  Jun. 2018, 人工知能学会全国大会 (JSAI 2018)


• 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

  松村昂輝, 沖本 天太, 平山 勝敏

  Jun. 2018, 人工知能学会全国大会 (JSAI 2018)


• 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

  小浦 隆之, 平山 勝敏, 沖本 天太

  Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 343 - 344


• 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

  宮田 直人, 平山 勝敏, 沖本 天太

  Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 351 - 352


• 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

  山中 悠介, 沖本 天太, 平山 勝敏

  Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 1, 335 - 336


• 共同研究チーム編成ツールの開発

  吉崎 大貴, 沖本 天太, 平山 勝敏

  Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 375 - 376


• 確率的な提携構造形成問題の解法

  松村 昂輝, 沖本 天太, 平山 勝敏

  Mar. 2018, 情報処理学会第80回全国大会 (IPSJ 2018), 2, 345 - 346


• Leximin Asymmetric Multiple Objective Distributed Constraint Optimization Problem

  Toshihiro Matsui, Hiroshi Matsuo, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo

  Blackwell Publishing Inc., Feb. 2018, Computational Intelligence, 34(1) (1), 49 - 84


• Stochastic Game Modelling for Distributed Constraint Reasoning with Privacy.

  Julien Savaux, Julien Vion, Sylvain Piechowiak, René, Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi

  2018, International Symposium on Artificial Intelligence and Mathematics, ISAIM 2018, Fort Lauderdale, Florida, USA, January 3-5, 2018.


• Study of Route Optimization Considering Bottlenecks and Fairness Among Partial Paths

  Toshihiro Matsui, Marius Silaghi, HIRAYAMA KATSUTOSHI, Makoto Yokoo, Hiroshi Matsuo

  SciTePress, Jan. 2018, Proceedings of the 10th International Conference on Agents and Artificial Intelligence (ICAART-2018), 37 - 47


• Area Protection in Adversarial Path-finding Scenarios with Multiple Mobile Agents on Graphs - A Theoretical and Experimental Study of Strategies for Defense Coordination

  Marika Ivanova, Pavel Surynek, HIRAYAMA KATSUTOSHI

  Jan. 2018, Proceedings of the 10th International Conference on Agents and Artificial Intelligence (ICAART-2018), 184 - 191


• Leximin Multiple Objective DCOPs on Factor Graphs for Preferences of Agents

  Toshihiro Matsui, Marius Silaghi, Tenda Okimoto, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  IOS Press, 2018, Fundamenta Informaticae, 158(1-3) (1-3), 63 - 91


• 確率的な提携構造形成フレームワークの提案

  沖本 天太, 平山 勝敏, Nicolas Schwind, 井上 克巳, Pierre Marquis

  Sep. 2017, 第16回情報科学技術フォーラム（FIT-2017）, 2, 65 - 70


• Distributed Stochastic Search Algorithm for Multi-ship Encounter Situations

  Donggyun Kim, Katsutoshi Hirayama, Tenda Okimoto

  Jul. 2017, JOURNAL OF NAVIGATION, 70(4) (4), 699 - 718

  Link to Kobe Univ. Repository (Kernel)


• 不確実性を考慮した提携構造形成問題に関する一検討

  沖本 天太, Nicolas Schwind, 平山 勝敏, 井上 克巳, Pierre Marquis

  May 2017, 人工知能学会全国大会 (JSAI 2017)


• 乗合バス路線に基づく災害ロードマップ作成

  伊角 愛結, 沖本 天太, 平山 勝敏, 酒井 裕規, 西村 悦子

  Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), 2, 355 - 356


• 制約充足問題におけるインフルエンシャル変数の特定

  浦地 勇人, 沖本 天太, 平山 勝敏, Nicolas Schwind, 井上 克巳, Pierre Marquis

  Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017)


• MC-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

  赤木 純, 平山 勝敏, 沖本 天太

  Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), 2, 45 - 46


• DMAT編成問題

  岸田 有平, 沖本 天太, 平山 勝敏

  Mar. 2017, 情報処理学会第79回全国大会 (IPSJ 2017), 2, 357 - 358


• Distributed Constraint Problems for Utilitarian Agents with Privacy Concerns, Recast as POMDPs.

  Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi 0001

  2017, CoRR, abs/1703.06939


• Utilitarian Approach to Privacy in Distributed Constraint Optimization Problems.

  Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi 0001

  AAAI Press, 2017, Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference(FLAIRS), 454 - 459


• Multi-objective Nurse Rerostering Problem

  Shih-Min Wu, Tenda Okimoto, Katsutoshi Hirayama, Katsumi Inoue

  2017, MULTI-AGENT AND COMPLEX SYSTEMS, 670, 139 - 152


• Multi-objective Nurse Rerostering Problem

  Shih-Min Wu, Tenda Okimoto, Katsutoshi Hirayama, Katsumi Inoue

  Springer Singapore, Nov. 2016, Multi-agent and Complex Systems, 139 - 152


• 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

  浦地 勇人, 沖本 天太, シュウィンド ニコラ, HIRAYAMA KATSUTOSHI, 井上 克巳

  Jun. 2016, 第30回人工知能学会全国大会 (JSAI 2016), 2, 623 - 624


• Distributed Stochastic Search Algorithm for n-Ship Collision Avoidance

  Donggyun Kim, Katsutoshi Hirayama, Tenda Okimoto

  Jun. 2016, 第30回人工知能学会全国大会 (JSAI 2016)


• A bundle method in distributed lagrangian relaxation protocol

  Kenta Hanada, Katsutoshi Hirayama, Tenda Okimoto

  Japanese Society for Artificial Intelligence, Feb. 2016, Transactions of the Japanese Society for Artificial Intelligence, 31(2) (2)


• 分散ラグランジュ緩和プロトコルにおけるバンドル法

  花田 研太, HIRAYAMA KATSUTOSHI, 沖本 天太

  Feb. 2016, 人工知能学会論文誌, 31(2) (2), pp.C - F75_1-10


• Bayesian network-based extension for PGP - Estimating petition support

  Marius Silaghi, Song Qui, Toshihiro Matsui, Makoto Yokoo, Katsutoshi Hirayama

  AAAI Press, 2016, Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016, 98 - 103


• DisCSPs with Privacy Recast as Planning Problems for Utility-based Agents.

  Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi 0001

  2016, CoRR, abs/1604.06790


• Utilitarian Distributed Constraint Optimization Problems.

  Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi 0001

  2016, CoRR, abs/1604.06787


• Privacité dans les DisCSP pour agents utilitaires.

  Julien Savaux, Julien Vion, Sylvain Piechowiak, René Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Marius Silaghi 0001

  Cépaduès Éditions, 2016, Systèmes Multi-Agents et simulation - Vingt-quatrièmes journées francophones sur les systèmes multi-agents(JFSMA), 129 - 138


• DisCSPs with Privacy Recast as Planning Problems for Self-Interested Agents

  Julien Savaux, Julien Vion, Sylvain Piechowiak, Rene Mandiau, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo, Shakre Elmane, Marius Silaghi

  2016, 2016 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2016), 359 - 366


• A Constraint Approach to Pivot-Based Bilingual Dictionary Induction

  Mairidan Wushouer, Donghui Lin, Toru Ishida, Katsutoshi Hirayama

  Jan. 2016, ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 15(1) (1)


• Skill-Based Dynamic Team Formation Problem

  Tenda Okimoto, Maxime Clement, Katsutoshi Hirayama, Katsumi Inoue

  Nov. 2015, The 16th International Symposium on Advanced Intelligent Systems (ISIS 2015), 781 - 793


• Distributed Stochastic Search Algorithm for n-Ship Collision Avoidance

  Donggyun Kim, Katsutoshi Hirayama, Tenda Okimoto

  Nov. 2015, The 16th International Symposium on Advanced Intelligent Systems (ISIS 2015), 1100 - 1112


• 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

  花田 研太, HIRAYAMA KATSUTOSHI, 沖本 天太

  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


• 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

  沖本 天太, HIRAYAMA KATSUTOSHI, 井上 克巳, 波多野 大督, 花田 研太, Maxime Clement, Tony Ribeiro, Shih-Min Wu

  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


• Favorable Solution in Multi-Objective Nurse Rerostering Problem

  OKIMOTO TENDA, Shih-Min Wu, Katsutoshi Hirayama, Katsumi Inoue

  Jul. 2015, In proceedings of the International Symposium on Scheduling 2015 (ISS-15), 109 - 114


• 多目的ナース・リスケジューリング問題における平等性

  呉 詩敏, 沖本 天太, 平山 勝敏, 井上克巳

  Jun. 2015, 第29回人工知能学会全国大会 (JSAI 2015)


• Egalitarianism in Multi-Objective Nurse Rerostering Problem

  呉 詩敏, OKIMOTO TENDA, HIRAYAMA KATSUTOSHI, 井上 克巳

  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


• Ship Collision Avoidance by Distributed Tabu Search

  Dong-Gyun Kim, Katsutoshi Hirayama, OKIMOTO TENDA

  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


• Max-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

  Hanada Kenta, Hirayama Katsutoshi, OKIMOTO TENDA

  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


• Ship Collision Avoidance by Distributed Tabu Search

  Dong-Gyun Kim, HIRAYAMA KATSUTOSHI, Tenda Okimoto

  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


• Effect of Bundle Method in Distributed Lagrangian Relaxation Protocol

  Kenta Hanada, Katsutoshi Hirayama, OKIMOTO TENDA

  Jan. 2015, The AAAI-15 Workshop on Planning, Search, and Optimization (PlanSOpt-15). In conjunction with AAAI-2015, 47 - 54


• Leximin Asymmetric Multiple Objective DCOP on Factor Graph

  Toshihiro Matsui, Marius Silaghi, Tenda Okimoto, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  2015, PRIMA 2015: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS, 9387, 134 - 151


• 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

  花田 研太, HIRAYAMA KATSUTOSHI, OKIMOTO TENDA

  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


• Collision Avoidance in Multiple-Ship Situations by Distributed Local Search

  Dong-Gyun Kim, HIRAYAMA KATSUTOSHI, Gyei-Kark Park

  Fuji Technology Press, Sep. 2014, Journal of Advanced Computational Intelligence and Intelligent Informatics, 18(5) (5), 839 - 848


• 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

  加藤 大貴, 花田 研太, HIRAYAMA KATSUTOSHI

  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


• Open census for addressing false identity attacks in agent-based decentralized social networks.

  Song Qin 0001, Marius-Calin Silaghi, Ihsan Hussien, Makoto Yokoo, Toshihiro Matsui, Katsutoshi Hirayama

  IFAAMAS/ACM, 2014, International conference on Autonomous Agents and Multi-Agent Systems(AAMAS), 1569 - 1570


• Bilingual Dictionary Induction as an Optimization Problem

  Mairidan Wushouer, Donghui Lin, Toru Ishida, Katsutoshi Hirayama

  2014, LREC 2014 - NINTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2122 - 2129


• Pivot-Based Bilingual Dictionary Extraction from Multiple Dictionary Resources

  Mairidan Wushouer, Donghui Lin, Toru Ishida, Katsutoshi Hirayama

  2014, PRICAI 2014: TRENDS IN ARTIFICIAL INTELLIGENCE, 8862, 221 - 234


• Leximin Multiple Objective Optimization for Preferences of Agents

  Toshihiro Matsui, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  2014, PRIMA 2014: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS, 8861, 423 - 438


• Computing a Payoff Division in the Least Core for MC-nets Coalitional Games

  Katsutoshi Hirayama, Kenta Hanada, Suguru Ueda, Makoto Yokoo, Atsushi Iwasaki

  2014, PRIMA 2014: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS, 8861, 319 - 332


• A Prototype of Geotagged Image Database on a P2P Agent Framework

  有吉 勇介, 鎌原 淳三, 平山 勝敏, 田中 直樹, 長松 隆, 寺西 裕一

  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


• 多層一般化相互割当問題の定式化とその解法

  HIRAYAMA KATSUTOSHI, 花田 研太

  <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

  Link to Kobe Univ. Repository (Kernel)


• Embedding Preference Ordering for Single-phase Self-stabilizing DCOP Solvers

  Matsui Toshihiro, Marius Silaghi, HIRAYAMA KATSUTOSHI, Yokoo Makoto, Matsuo Hiroshi

  Dec. 2013, Proceedings of the 16th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2013)


• Ship Collision Avoidance using Distributed Local Search

  Dong-Gyun Kim, HIRAYAMA KATSUTOSHI, Gyei-Kark Park

  Nov. 2013, Proceedings of the 14th International Symposium on Advanced Intelligent Systems(ISIS 2013)


• DeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP

  Hatano Daisuke, HIRAYAMA KATSUTOSHI

  Aug. 2013, Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013), 566 - 572


• 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

  神谷 竜平, 花田 研太, HIRAYAMA KATSUTOSHI

  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


• SATによる車両運用計画問題の定式化と集中／分散解法

  下牧 昌太郎, 尾松 郁哉, HIRAYAMA KATSUTOSHI

  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


• Multi-MaxSATにおけるバンドル法の効果

  花田 研太, HIRAYAMA KATSUTOSHI

  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


• Addressing False Identity Attacks in Action-Based P2P Social Networks with an Open Census.

  Song Qin 0001, Marius-Calin Silaghi, Toshihiro Matsui, Makoto Yokoo, Katsutoshi Hirayama

  IEEE Computer Society, 2013, 2013 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 50 - 57


• Dynamic CSP with decision transition costs and its solutions

  Hatano Daisuke, Hirayama Katsutoshi

  2013, Transactions of the Japanese Society for Artificial Intelligence, 28(1) (1), 34 - 42

  Link to Kobe Univ. Repository (Kernel)


• Embedding preference ordering for symmetric DCOP solvers on spanning trees

  Toshihiro Matsui, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  2013, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8291, 197 - 212


• DirectDemocracyP2P-Decentralized Deliberative Petition Drives

  Marius C. Silaghi, Khalid Alhamed, Osamah Dhannoon, Song Qin, Rahul Vishen, Ryan Knowles, Ihsan Hussien, Yi Yang, Toshihiro Matsui, Makoto Yokoo, Katsutoshi Hirayama

  2013, 13TH IEEE INTERNATIONAL CONFERENCE ON PEER-TO-PEER COMPUTING (P2P)


• DeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP (Extended Abstract)

  Daisuke Hatano, Katsutoshi Hirayama

  2013, Proceedings of the 12th International Conference on Autonomous Agents & Multi-agent Systems (AAMAS-2013), 1325 - 1326


• 値推移コスト付き動的制約充足問題とその解法

  HATANO DAISUKE, HIRAYAMA KATSUTOSHI

  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

  Link to Kobe Univ. Repository (Kernel)


• Distributed search methods for Quantified Distributed Constraint Optimization Problem

  Toshihiro Matsui, Marius C. Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  社団法人人工知能学会, 2013, Transactions of the Japanese Society for Artificial Intelligence, 28(1) (1), 43 - 56


• Location-dependent Content-based Image Retrieval System Based on a P2P Mobile Agent Framework

  Yusuke Ariyoshi, Junzo Kamahara, Naoki Tanaka, Katsutoshi Hirayama, Takashi Nagamatsu, Yuuichi Teranishi

  2013, 2013 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS), 72 - 77


• Distributed Lagrangian Relaxation Protocol for the Over-constrained Generalized Mutual Assignment Problem

  HANADA KENTA, HIRAYAMA KATSUTOSHI

  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

  Link to Kobe Univ. Repository (Kernel)


• Soft Nonlinearity Constraints and their Lower-Arity Decomposition.

  Venkatesh Ramamoorthy, Marius Silaghi 0001, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo

  2012, International Symposium on Artificial Intelligence and Mathematics(ISAIM)


• Distributed search method with bounded cost vectors on multiple objective DCOPs

  Toshihiro Matsui, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  2012, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7455, 137 - 152


• Interactive algorithm for multi-objective constraint optimization

  Tenda Okimoto, Yongjoon Joe, Atsushi Iwasaki, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo

  2012, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7514, 561 - 576


• Design of GeoConscious P2P Content-based Image Retrieval

  Junzo Kamahara, Naoki Tanaka, Katsutoshi Hirayama, Takashi Nagamatsu, Yuuichi Teranishi, Yusuke Ariyoshi

  2012, 2012 SEVENTH INTERNATIONAL CONFERENCE ON BROADBAND, WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS (BWCCA 2012), 82 - 87


• 値変更コスト付き動的SATの定式化とその解法

  波多野 大督, 平山 勝敏

  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

  Link to Kobe Univ. Repository (Kernel)


• Coalition structure generation based on distributed constraint optimization

  Suguru Ueda, Atsushi Iwasaki, Makoto Yokoo, Marius C. Silaghi, Katsutoshi Hirayama, Toshihiro Matsui

  2011, Transactions of the Japanese Society for Artificial Intelligence, 26(1) (1), 179 - 189


• Adaptive price update in distributed Lagrangian relaxation protocol

  Katsutoshi Hirayama, Toshihiro Matsui, Makoto Yokoo

  2011, Transactions of the Japanese Society for Artificial Intelligence, 26(1) (1), 59 - 67


• Cooperative problem solving against adversary: Quantified distributed constraint satisfaction problem

  Satomi Baba, Atsushi Iwasaki, Makoto Yokoo, Marius C. Silaghi, Katsutoshi Hirayama, Toshihiro Matsui

  2011, Transactions of the Japanese Society for Artificial Intelligence, 26(1) (1), 136 - 146


• 分散制約最適化問題に基づく提携構造形成問題

  上田 俊, 岩崎 敦, 横尾 真, Marius C. Silaghi, 平山 勝敏, 松井 俊浩

  Jan. 2011, 人工知能学会論文誌, Vol.26, No.1, pp.179--189


• 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

  平山 勝敏, 松井 俊浩, 横尾 真

  Jan. 2011, 人工知能学会論文誌, Vol.26, No.1, pp.59--67


• 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

  馬場 里美, 岩崎 敦, 横尾 真, Marius C. Silaghi, 平山 勝敏, 松井 俊浩

  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


• Dynamic SAT with decision change costs: Formalization and solutions

  Daisuke Hatano, Katsutoshi Hirayama

  2011, IJCAI International Joint Conference on Artificial Intelligence, pp.560--565, 560 - 565


• The design of cryptographic S-boxes using CSPs

  Venkatesh Ramamoorthy, Marius C. Silaghi, Toshihiro Matsui, Katsutoshi Hirayama, Makoto Yokoo

  2011, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6876, 54 - 68


• Reducing the search space of resource constrained DCOPs

  Toshihiro Matsui, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Boi Faltings, Hiroshi Matsuo

  2011, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6876, 576 - 590


• Distributed Lagrangian Relaxation Protocol for the Over-constrained Generalized Mutual Assignment Problem

  Kenta Hanada, Katsutoshi Hirayama

  2011, AGENTS IN PRINCIPLE, AGENTS IN PRACTICE, 7047, 174 - 186


• A Quantified Distributed Constraint Optimization Problem

  MATSUI Toshihiro, YOKOO Makoto, BABA Satomi, SILAGHI Marius C, HIRAYAMA Katsutoshi, MATSUO Hiroshi

  May 2010, Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-2010), pp.1023–1030, 1023 - 1030


• 分散制約最適化問題へのソフトアーク整合の適用

  MATSUI Toshihiro, SILAGHI Marius C, HIRAYAMA Katsutoshi, YOKOO Makoto, MATSUO Hiroshi

  Mar. 2010, 人工知能学会論文誌, Vol.25, No.3, pp.410-422


• Applying soft arc consistency to distributed constraint optimization problems

  Toshihiro Matsui, Marius C. Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  2010, Transactions of the Japanese Society for Artificial Intelligence, 25(3) (3), 410 - 422


• Coalition Structure Generation Based on Distributed Constraint Optimization

  Suguru Ueda, Atsushi Iwasaki, Makoto Yokoo, Marius Calin Silaghi, Katsutoshi Hirayama, Toshihiro Matsui

  2010, PROCEEDINGS OF THE TWENTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-10), pp.197--203, 197 - 203


• 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

  MATSUI Toshihiro, SILAGHI Marius C, HIRAYAMA Katsutoshi, YOKOO Makoto, MATSUO Hiroshi

  Jul. 2009, 人工知能学会論文誌, Vol.24, No.5, pp.417-427


• Directed Soft Arc Consistency in Pseudo Trees

  MATSUI Toshihiro, SILAGHI Marius C, HIRAYAMA Katsutoshi, YOKOO Makoto, MATSUO Hiroshi

  May 2009, Proceedings of the 8th International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS-2009), pp.1065-1072, 1065 - 1072


• A resource constrained distributed constraint optimization method using resource constraint free pseudo-tree

  Toshihiro Matsui, Marius C. Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  Japanese Society for Artificial Intelligence, 2009, Transactions of the Japanese Society for Artificial Intelligence, 24(5) (5), 417 - 427


• Multi-MaxSAT: ラグランジュ分解・調整法を用いたWeighted Max-SATの解法

  KURODA Akiyuki, HIRAYAMA Katsutoshi

  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

  Link to Kobe Univ. Repository (Kernel)


• Resource Constrained Distributed Constraint Optimization with Virtual Variables

  MATSUI Toshihiro, SILAGHI Marius C, HIRAYAMA Katsutoshi, YOKOO Makoto, MATSUO Hiroshi

  AAAI Press, Jul. 2008, Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI-2008), pp.120-125, 120 - 125


• Resource constrained distributed constraint optimization using resource constraint free pseudo-tree

  Toshihiro Matsui, Marius Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo

  IFAAMAS, May 2008, The Seventh International Conference on Autonomous Agents and Multi-agent Systems (AAMAS2008), 1(1) (1), 1405 - 1408


• An α-approximation Protocol for the Generalized Mutual Assignment Problem

  HIRAYAMA Katsutoshi

  Jul. 2007, Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-2007), pp.744-749


• DisLRP_alpha: alpha-approximation in Generalized Mutual Assignment

  HIRAYAMA KATSUTOSHI

  2007, PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS


• An alpha-approximation Protocol for the Generalized Mutual Assignment Problem

  HIRAYAMA KATSUTOSHI

  2007, Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence


• A New Approach to Distributed Task Assignment using Lagrangian Decomposition and Distributed Constraint Satisfaction

  HIRAYAMA Katsutoshi

  Jul. 2006, Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-2006), pp.660-665


• Distributed lagrangean relaxation protocol for the generalized mutual assignment problem

  Katsutoshi Hirayama

  2006, Proceedings of the International Conference on Autonomous Agents, 2006, 890 - 892

  Link to Kobe Univ. Repository (Kernel)


• Distributed Lagrangean Relaxation Protocol for the Generalized Mutual Assignment Problem

  HIRAYAMA Katsutoshi

  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

  Link to Kobe Univ. Repository (Kernel)


• The distributed breakout algorithms

  K Hirayama, M Yokoo

  Jan. 2005, ARTIFICIAL INTELLIGENCE, 161(1-2) (1-2), 89 - 115


• Secure distributed constraint satisfaction: reaching agreement without revealing private information

  M Yokoo, K Suzuki, K Hirayama

  Jan. 2005, ARTIFICIAL INTELLIGENCE, 161(1-2) (1-2), 229 - 245


• An Easy-Hard-Easy Cost Profile in Distributed Constraint Satisfaction

  HIRAYAMA Katsutoshi, YOKOO Makoto, SYCARA Katia

  Sep. 2004, IPSJ Journal, Vol.45, No.9, pp.2217-2225


• On market-inspired approaches to propositional satisfiability

  WE Walsh, M Yokoo, K Hirayama, MP Wellman

  Mar. 2003, ARTIFICIAL INTELLIGENCE, 144(1-2) (1-2), 125 - 156


• Secure Distributed Constraint Satisfaction: Reaching Agreement without Revealing Private Information

  YOKOO Makoto, SUZUKI Koutarou, HIRAYAMA Katsutoshi

  Springer, Sep. 2002, Proceedings of the Eighth International Conference on Principles and Practice of Constraint Programming (CP-2002), pp.387--401, 387 - 401


• Local Search for Distributed SAT with Complex Local Problems

  HIRAYAMA Katsutoshi, YOKOO Makoto

  Jul. 2002, Proceedings of the First International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS-2002), pp.1199--1206, 1199 - 1206


• On Market-Inspired Approaches to Propositional Satisfiability

  WALSH William E, YOKOO Makoto, HIRAYAMA Katsutoshi, WELLMAN Michael P

  Aug. 2001, Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI-2001), pp.1152-1158(1-2) (1-2), 125 - 156


• Algorithms for distributed constraint satisfaction: A review

  M Yokoo, K Hirayama

  Jun. 2000, AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 3(2) (2), 185 - 207


• 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

  YOKOO Makoto, HIRAYAMA Katsutoshi

  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


• The Effect of Nogood Learning in Distributed Constraint Satisfaction

  HIRAYAMA Katsutoshi, YOKOO Makoto

  Apr. 2000, Proceedings of the 20th IEEE International Conference on Distributed Computing Systems (ICDCS-2000), pp.169-177, 169 - 177


• 分散制約充足におけるnogood学習の効果

  HIRAYAMA Katsutoshi, YOKOO Makoto

  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


• 複雑な局所問題に対応する分散制約充足アルゴリズム

  YOKOO Makoto, HIRAYAMA Katsutoshi

  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


• The Phase Transition in Distributed Constraint Satisfaction Problems: Fist Results.

  Katsutoshi Hirayama, Makoto Yokoo, Katia P. Sycara

  Springer, 2000, Principles and Practice of Constraint Programming - CP 2000(CP), 515 - 519


• Frequency assignment for cellular mobile systems using constraint satisfaction techniques

  M Yokoo, K Hirayama

  2000, 2000 IEEE 51ST VEHICULAR TECHNOLOGY CONFERENCE, PROCEEDINGS, VOLS 1-3, pp.888--894, 888 - 894


• An approach to over-constrained distributed constraint satisfaction problems: Distributed hierarchical constraint satisfaction

  K Hirayama, M Yokoo

  2000, FOURTH INTERNATIONAL CONFERENCE ON MULTIAGENT SYSTEMS, PROCEEDINGS, pp.135-142, 135 - 142


• Frequency assignment for cellular mobile systems using constraint satisfaction techniques

  Makoto Yokoo, Katsutoshi Hirayama

  Springer Verlag, 1999, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1713, 490 - 491


• 分散不完全制約充足問題

  HIRAYAMA Katsutoshi, YOKOO Makoto

  Jan. 1999, 人工知能学会誌, Vol.14, No.4, pp.636-645


• 分散breakout：反復改善型分散制約充足アルゴリズム

  YOKOO Makoto, HIRAYAMA Katsutoshi

  Jun. 1998, 情報処理学会論文誌, Vol.39, No.6, pp.1889-1897(6) (6), 1889 - 1897


• Distributed constraint satisfaction algorithm for complex local problems

  M Yokoo, K Hirayama

  1998, INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS, PROCEEDINGS, pp.372-379, 372 - 379


• Distributed partial constraint satisfaction problem

  K Hirayama, M Yokoo

  1997, PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING - CP 97, 1330, 222 - 236


• Distributed Breakout Algorithm for Solving Distributed Constraint Satisfaction Problems

  YOKOO Makoto, HIRAYAMA Katsutoshi

  Dec. 1996, Proceedings of Second International Conference on Multiagent Systems (ICMAS-1996), pp.401-408, 401 - 408


• 分散制約充足におけるエージェントの非集中的組織化

  HIRAYAMA Katsutoshi, YAMADA Seiji, TOYODA Junichi

  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


• Forming Coalitions for Breaking Deadlocks

  HIRAYAMA Katsutoshi, TOYODA Junichi

  Jun. 1995, Proceedings of First International Conference on Multiagent Systems (ICMAS-1995), pp.155-162, 155 - 162


• 山登り法を用いた分散制約充足における組織化

  HIRAYAMA Katsutoshi, YAMADA Seiji, TOYODA Junichi

  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

• 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

  HIRAYAMA KATSUTOSHI, MATSUI TOSHIHIRO

  人工知能学会, May 2013, 人工知能学会誌, 28(3) (3), 380 - 388, Japanese

  [Refereed]

  Introduction scientific journal


• 国際シンポジウムFLOPS 2012開催報告

  田村 直之, 番原 睦則, 平山 勝敏, 宋 剛秀

  Mar. 2013, コンピュータソフトウェア, 30(1):16-19, Japanese

  [Refereed]

  Others


• 国際シンポジウムFLOPS2012開催報告

  田村 直之, 番原 睦則, HIRAYAMA KATSUTOSHI, 宋剛秀

  Mar. 2013, コンピュータソフトウエア, 30(1) (1), 16 - 19, Japanese

  [Refereed]

  Meeting report


• Centralized and Distributed SAT for the Rolling Stock Operation Problem

  下牧 昌太郎, 尾松 郁哉, 平山 勝敏

  人工知能学会, 2013, 人工知能学会全国大会論文集, 27, 1 - 4, Japanese


• OS-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))

  平山 勝敏, 平山 勝敏

  01 Nov. 2012, 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence, 27(6) (6), 650 - 650, Japanese


• Distributed Optimization Problems and Their Solutions for Multi-Agent Systems

  平山 勝敏

  人工知能学会, 02 Feb. 2012, 人工知能基本問題研究会, 85, 19 - 21, Japanese


• Asynchronous Backtracking Algorithms for Clause-set Partitioned Distributed SAT

  下牧 昌太郎, 平山 勝敏

  人工知能学会, 2012, 人工知能学会全国大会論文集, 26, 1 - 4, Japanese


• DeQED : DCOP Solving by Exchanging Dual Variables

  波多野 大督, 平山 勝敏

  人工知能学会, 2012, 人工知能学会全国大会論文集, 26, 1 - 4, Japanese


• Dynamic CSP with Decision Change Costs : Formalization and Solutions

  波多野 大督, 平山 勝敏

  人工知能学会, 2011, 人工知能学会全国大会論文集, 25, 1 - 4, Japanese


• *-SAT: Extentions of SAT(Recent Advances in SAT Techniques)

  HIRAYAMA Katsutoshi, YOKOO Makoto, Katsutoshi Hirayama, Makoto Yokoo, Graduate School of Maritime Sciences Kobe University, Graduate School of Information Science and Electrical Engineering Kyushu University

  人工知能学会, 01 Jan. 2010, Journal of Japanese Society for Artificial Intelligence, 25(1) (1), 105 - 113, Japanese


• *-SAT: SATの拡張

  HIRAYAMA Katsutoshi, YOKOO Makoto

  Jan. 2010, 人工知能学会誌, Vol.25, No.1, pp.105-113, Japanese

  Introduction scientific journal


• Distributed 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)

  Hirayama Katsutoshi

  人工知能学会, 04 Dec. 2004, 知識ベ-スシステム研究会, 67, 73 - 78, English


• 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)

  平山 勝敏

  人工知能学会, 01 Mar. 2004, 知識ベ-スシステム研究会, 64, 183 - 188, Japanese


• Distributed Task Assignment for Information Gathering

  HIRAYAMA Katsutoshi, KITAMURA Yasuhiko

  This 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 Gathering

  HIRAYAMA Katsutoshi, KITAMURA Yasuhiko

  This 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 Integration

  HIRAYAMA Katsutoshi, KITAMURA Yasuhiko

  We 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


• Development of Environmental Definition Watcher System

  KAJITANI Toshiaki, HIRAYAMA Katsutoshi

  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, Japanese


• CSPの新しい展開：分散／動的／不完全CSP

  YOKOO Makoto, HIRAYAMA Katsutoshi

  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, Japanese

  Introduction scientific journal


• ICMAS'95報告

  平山 勝敏, 横尾 真

  一般社団法人情報処理学会, 15 Sep. 1995, 情報処理, 36(9) (9), 893 - 895, Japanese


• Balancing an Organizing Load in Distributed Constraint Satisfaction

  HIRAYAMA Katsutoshi, YAMADA Seiji, TOYODA Jun'ichi

  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, Japanese


• 描画用制約プログラミング言語 : CLDの設計

  平山 勝敏, 山田 誠二, 辻 三郎

  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

• Distributed Ship Collision Avoidance Algorithms

  Katsutoshi Hirayama, Donggyun Kim, Kazuma Gohara, Tenda Okimoto, Koki Miyake, Tomohiro Shiota

  9th International Conference on Advanced Intelligent Maritime Safety and Technology (Ai-MAST 2023), Nov. 2023, English

  [Invited]

  Keynote oral presentation


• 分散船舶衝突回避アルゴリズム

  平山勝敏

  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

  [Invited]

  Invited oral presentation


• 深層強化学習による最適な分散衝突回避

  郷原 一眞, 平山 勝敏, 沖本 天太, キム ドンギュン

  5th Symposium on Multi Agent Systems for Harmonization 2022（SMASH22 Winter Symposium), Feb. 2022, Japanese

  Oral presentation


• レジリエントなナース・スケジューリング問題

  沖本 天太, 平山 勝敏, 番原 睦則, 井上 克巳

  第17回科学技術フォーラム (FIT-2018), Sep. 2018, Japanese, Domestic conference

  Oral presentation


• 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

  沖本 天太, 上田 俊, 平山 勝敏, 藤本 真育, 豊島 大弥

  第17回科学技術フォーラム (FIT-2018), Sep. 2018, Japanese, Domestic conference

  Oral presentation


• 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

  唐渡 裕基, 平山 勝敏, 沖本 天太, 金 東均

  人工知能学会全国大会 (JSAI 2018), Jun. 2018, Japanese, Domestic conference

  Oral presentation


• 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

  松村 昂輝, 沖本 天太, 平山 勝敏

  人工知能学会全国大会 (JSAI 2018), Jun. 2018, Japanese, Domestic conference

  Oral presentation


• 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

  小浦 隆之, 平山 勝敏, 沖本 天太

  情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference

  Oral presentation


• 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

  宮田 直人, 平山 勝敏, 沖本 天太

  情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference

  Oral presentation


• 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

  山中 悠介, 沖本 天太, 平山 勝敏

  情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference

  Oral presentation


• 共同研究チーム編成ツールの開発

  吉崎 大貴, 沖本 天太, 平山 勝敏

  情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference

  Oral presentation


• 確率的な提携構造形成問題の解法

  松村 昂輝, 沖本 天太, 平山 勝敏

  情報処理学会第80回全国大会 (IPSJ 2018), Mar. 2018, Japanese, Domestic conference

  Oral presentation


• MC-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

  HIRAYAMA KATSUTOSHI, 赤木 純, OKIMOTO TENDA

  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 conference

  Oral presentation


• MC-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

  HIRAYAMA KATSUTOSHI, 赤木 純, OKIMOTO TENDA

  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 conference

  Oral presentation


• 乗合バス路線に基づく災害ロードマップ作成

  伊角 愛結, 沖本 天太, 平山 勝敏, 酒井 裕規, 西村 悦子

  情報処理学会第79回全国大会 (IPSJ 2017), Mar. 2017, Japanese, Domestic conference

  Oral presentation


• MC-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

  赤木 純, 平山 勝敏, 沖本 天太

  情報処理学会第79回全国大会 (IPSJ 2017), Mar. 2017, Japanese, Domestic conference

  Oral presentation


• DMAT編成問題

  岸田 有平, 沖本 天太, 平山 勝敏

  情報処理学会第79回全国大会 (IPSJ 2017), Mar. 2017, Japanese, Domestic conference

  Oral presentation


• 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

  浦地 勇人, OKIMOTO TENDA, シュウィンド ニコラ, HIRAYAMA KATSUTOSHI, 井上 克巳

  2016年度人工知能学会全国大会（第30回） (JSAI-2016), Jun. 2016, Japanese, Domestic conference

  Oral presentation


• Distributed Stochastic Search Algorithm for n-Ship Collision Avoidance

  Dong-Gyun Kim, Katsutoshi Hirayama, Tenda Okimoto

  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 conference

  Oral presentation


• Distributed Stochastic Search Algorithm for n-Ship Collision Avoidance

  HIRAYAMA KATSUTOSHI, Dong-Gyun Kim, Tenda Okimoto

  The 16th International Symposium on Advanced Intelligent Systems (ISIS-2015), Nov. 2015, English, Mokpo, Korea, International conference

  Poster presentation


• Multi-Objective Nurse Rerostering Problem

  Shih-Min Wu, Tenda Okimoto, HIRAYAMA KATSUTOSHI, Katsumi Inoue

  International Joint Agents Workshop and Symposium (IJAWS-2015), Oct. 2015, English, Kaga, Japan., International conference

  Oral presentation


• 多目的ナース・リスケジューリング問題における平等性

  呉 詩敏, OKIMOTO TENDA, HIRAYAMA KATSUTOSHI, 井上 克巳

  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

  Oral presentation


• Ship Collision Avoidance by Distributed Tabu Search

  Dong-Gyun Kim, HIRAYAMA KATSUTOSHI, Tenda Okimoto

  2015年度人工知能学会全国大会（第29回）, May 2015, English, 函館, Domestic conference

  Oral presentation


• Pivot-based Bilingual Dictionary Extraction from Multiple Dictionary Resources

  Mairidan Wushouer, Donghui Lin, Toru Ishida, HIRAYAMA KATSUTOSHI

  Proceedings of the 13th Pacific Rim International Conference on Artificial Intelligence (PRICAI-2014), Dec. 2014, English, Gold Coast, Australia, International conference

  Oral presentation


• Leximin Multiple Objective Optimization for Preferences of Agents

  Toshihiro Matsui, Marius Silaghi, HIRAYAMA KATSUTOSHI, Makoto Yokoo, Hiroshi Matsuo

  Proceedings of the 17th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2014), Dec. 2014, English, Gold Coast, Australia, International conference

  Oral presentation


• Computing a Payoff Division in the Least Core for MC-nets Coalitional Games

  HIRAYAMA KATSUTOSHI, Kenta Hanada, Suguru Ueda, Makoto Yokoo, Atsushi Iwasaki

  Proceedings of the 17th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2014), Dec. 2014, English, Gold Coast, Australia, International conference

  Oral presentation


• 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

  加藤 大貴, 花田 研太, HIRAYAMA KATSUTOSHI

  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

  Oral presentation


• Bilingual Dictionary Induction as an Optimization Problem

  Mairidan Wushouer, Toru Ishida, Donghui Lin, HIRAYAMA KATSUTOSHI

  Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014), May 2014, English, Reykjavik, Iceland, International conference

  Oral presentation


• Embedding Preference Ordering for Symmetric DCOP Solvers on Spanning Trees

  Toshihiro Matsui, Marius Silaghi, HIRAYAMA KATSUTOSHI, Makoto Yokoo, Hiroshi Matsuo

  Proceedings of the 16th International Conference on Principles and Practice of Multi-Agent Systems (PRIMA-2013), Dec. 2013, English, Dunedin, New Zealand, International conference

  Oral presentation


• Ship Collision Avoidance using Distributed Local Search

  Dong-Gyun Kim, HIRAYAMA KATSUTOSHI, Gyei-Kark Park

  Proceedings of the 14th International Symposium on Advanced Intelligent Systems, Nov. 2013, English, Daejeon, Korea, International conference

  Public symposium


• DeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP

  Daisuke Hatano, HIRAYAMA KATSUTOSHI

  Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-2013), Aug. 2013, English, Beijing, China, International conference

  Oral presentation


• 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

  神谷 竜平, HANADA KENTA, HIRAYAMA KATSUTOSHI

  2013年度人工知能学会全国大会（第27回）, Jun. 2013, Japanese, 富山, Domestic conference

  Oral presentation


• SATによる車両運用計画問題の定式化と集中／分散解法

  下牧 昌太郎, 尾松 郁哉, HIRAYAMA KATSUTOSHI

  2013年度人工知能学会全国大会（第27回）, Jun. 2013, Japanese, 富山, Domestic conference

  Oral presentation


• Multi-MaxSATにおけるバンドル法の効果

  HANADA KENTA, HIRAYAMA KATSUTOSHI

  2013年度人工知能学会全国大会（第27回）, Jun. 2013, Japanese, 富山, Domestic conference

  Oral presentation


• 多層一般化相互割当問題の定式化とその解法

  HANADA KENTA, HIRAYAMA KATSUTOSHI

  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

  Oral presentation


• DeQED: 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

  HATANO DAISUKE, HIRAYAMA KATSUTOSHI

  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

  Oral presentation


• 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

  下牧 昌太郎, HIRAYAMA KATSUTOSHI

  2012年度人工知能学会全国大会（第26回）, Jun. 2012, Japanese, 山口, Domestic conference

  Oral presentation


• DeQED: 双対変数の値を交換する分散制約最適化アルゴリズム

  HATANO DAISUKE, HIRAYAMA KATSUTOSHI

  2012年度人工知能学会全国大会（第26回）, Jun. 2012, Japanese, 山口, Domestic conference

  Oral presentation


• 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

  平山 勝敏

  人工知能基本問題研究会（第85回）, Feb. 2012, Japanese, 下呂, Domestic conference

  Invited oral presentation


• Symmetry of Nonlinearity Constraints

  Venkatesh Ramamoorthy, Marius Silaghi, MATSUI Toshihiro, HIRAYAMA Katsutoshi, YOKOO Makoto

  Proceedings of the 11th International Workshop on Symmetry in Constraint Satisfaction Problems (SymCon-11), Sep. 2011, English, Perugia, Italy, International conference

  Oral presentation


• Soft Nonlinearity Constraints and their Lower-Arity Decomposition

  Venkatesh Ramamoorthy, Marius Silaghi, MATSUI Toshihiro, HIRAYAMA Katsutoshi, YOKOO Makoto

  Proceedings of the 11th Workshop on Preferences and Soft Constraints (SofT-11), Sep. 2011, English, Perugia, Italy, International conference

  Oral presentation


• 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

  谷口 賀則, 平山 勝敏

  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

  Oral presentation


• 値変更コスト付き動的CSPの定式化とその解法

  波多野 大督, 平山 勝敏

  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

  Oral presentation


• 値変更コスト付き動的SATのためのモデル追跡

  波多野 大督, 杉本 雄太, 平山 勝敏

  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

  Oral presentation


• 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

  花田 研太, 平山 勝敏

  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

  Oral presentation


• Model Tracking for Dynamic SAT with Decision Change Costs

  HIRAYAMA Katsutoshi, HATANO Daisuke, SUGIMOTO Yuta

  Proceedings of the 10th Workshop on Preferences and Soft Constraints (SofT-10), Sep. 2010, English, St.Andrews, Scotland, International conference

  Oral presentation


• 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

  HIRAYAMA Katsutoshi, MATSUI Toshihiro, YOKOO Makoto

  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

  Oral presentation


• 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

  SHIMOYANAGITA Koji, HIRAYAMA Katsutoshi

  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

  Oral presentation


• Multi-MaxSAT: ラグランジュ分解・調整法を用いたMax-SATの解法

  KURODA Akiyuki, HIRAYAMA Katsutoshi

  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

  Oral presentation


• A Distributed Solution Protocol that Computes an Upper Bound for the Generalized Mutual Assignment Problem

  HIRAYAMA Katsutoshi

  Seventh International Workshop on Distributed Constraint Reasoning, May 2006, English, Hakodate, International conference

  Oral presentation


• A Distributed Lagrangean Relaxation Protocol that Computes a Upper Bound

  HIRAYAMA Katsutoshi

  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 conference

  Oral presentation


• Realtime Dynamic Constraint Satisfaction Problem: formalization and solving method

  MATSUSHITA Toshinobu, YOKOO Makoto, HIRAYAMA Katsutoshi

  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 conference

  Oral presentation


• Distributed Lagrangean Relaxation Protocol for the Generalized Mutual Assignment Problem

  HIRAYAMA Katsutoshi

  First International Workshop on Distributed and Speculative Constraint Processing, Oct. 2005, English, Sitges, Spain, International conference

  Oral presentation


• ポアソンSAT過程における節の脆弱度と期待寿命

  平山 勝敏

  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

  Oral presentation

• American Association for Artificial Intelligence


• 日本オペレーションズ・リサーチ学会


• 人工知能学会


• 情報処理学会


• 電子情報通信学会

• 全体最適と個人最適を両立させる分散協調問題解決

  平山 勝敏, 沖本 天太, 松井 俊浩

  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


• 動的環境におけるロバストなチーム編成に関する研究

  沖本 天太

  科学研究費補助金／基盤研究(B), Apr. 2017 - Mar. 2021

  Competitive research funding


• 次世代型自動衝突回避システムのための基盤技術の創出

  平山 勝敏

  学術研究助成基金助成金／基盤研究(C), Apr. 2017 - Mar. 2020, Principal investigator

  Competitive research funding


• 海上・航空コンテナのハイブリッド型回送ネットワークシステムの構築

  今井 昭夫

  科学研究費補助金／基盤研究(B), Apr. 2017 - Mar. 2020

  Competitive research funding


• Establishing Theory of Resource Allocation Mechanism Design for Sustainable Development

  Yokoo Makoto, KOJIMA Fuhito, OBARA Ichiro

  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. 2017

  How 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.


• Next Generation P2P video streaming system with high quality and low power.

  MATSUO Hiroshi, MATSUI Toshihiro, TSUMURA Tomoaki, HIRAYAM Katsutoshi, YOKOO Makoto

  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 - 2011

  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.


• 分散グリーンコンピューティング：分散最適化技術の環境関連問題への応用

  平山 勝敏

  科学研究費補助金／基盤研究(B), 2011, Principal investigator

  Competitive research funding


• SATにおける高度な制約伝播と並列マルチエージェントプラニング

  平山 勝敏

  特別研究員奨励費, 2011, Principal investigator

  Competitive research funding


• 位置情報付き画像の分散エージェント管理による内容ベース画像検索とその応用

  鎌原 淳三

  科学研究費補助金／基盤研究(B), 2010

  Competitive research funding


• 制約最適化問題のＳＡＴ変換による解法とその並列分散処理に関する研究

  田村 直之

  科学研究費補助金／基盤研究(A), 2008

  Competitive research funding


• ユビキタス時代における次世代型電子商取引システムのための基盤技術

  平山 勝敏

  科学研究費補助金／基盤研究(B), 2007, Principal investigator

  Competitive research funding


• モルフォロジィーを用いた路面画像からの路面要素の認識に関する研究

  田中 直樹

  科学研究費補助金／基盤研究(C), 2005

  Competitive research funding


• 分散動的情報源からのアクティブ情報収集

  北村 泰彦, 平山 勝敏

  日本学術振興会, 科学研究費助成事業, 特定領域研究, 2001 - 2004

  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.


• Character and Line Figure Recognition in an Image

  TANAKA Naoki, HIRAYAMA Katsutoshi, MAEBA Takashi

  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 - 2000

  The 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.