Publications

2022

  • Ensemble Method using Real Images, Metadata and Synthetic Images for Control of Class Imbalance in Classification. Rogers Aloo, Atsuko Mutoh, Koichi Moriyama (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Nobuhiro Inuzuka (Nagoya Institute of Technology). 27th International Symposium on Artificial Life and Robotics (AROB 27th 2022), GS17-3 (2022). Beppu, Japan, Jan 27, 2022.
  • A Proposal for an Island Model by Exchange of Pheromone Graph Between Swarms in MAX-MIN Ant Syste. Keiichiro Takashiba, Atsuko Mutoh, Koichi Moriyama (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Nobuhiro Inuzuka (Nagoya Institute of Technology). 27th International Symposium on Artificial Life and Robotics (AROB 27th 2022), GS30-4 (2022). Beppu, Japan, Jan 25, 2022.

2021

  • Evaluation of Martial Arts Demonstration Focusing on Peak Timing Using Acceleration Data. Shohei Yamanaka, Kosuke Shima, Atsuko Mutoh, Koichi Moriyama (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Nobuhiro Inuzuka (Nagoya Institute of Technology). 2021 IEEE 10th Global Conference on Consumer Electronics (IEEE GCCE 2021), pp. 363-367 (2021). Kyoto, Japan, Oct. 13, 2021.
  • Classification of Buzzwords by Focusing on Time Trends Using Twitter Data. Juno Hashimoto, Atsuko Mutoh, Koichi Moriyama, Azusa Yokogoshi and Eiko Yoshida (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Nobuhiro Inuzuka (Nagoya Institute of Technology). 2021 IEEE 10th Global Conference on Consumer Electronics (IEEE GCCE 2021), pp. 368-370 (2021). Kyoto, Japan, Oct. 13, 2021.
  • Extraction of Behavioral Patterns by Recombining Non-Negative Multiple Matrix Factorization and Clustering Results. Shogo Yasui, Atsuko Mutoh, Koichi Moriyama (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University); Nobuhiro Inuzuka (Nagoya Institute of Technology). 2021 IEEE 10th Global Conference on Consumer Electronics (IEEE GCCE 2021), pp. 563-566 (2021). Kyoto, Japan, Oct. 13, 2021.

2020

2019

  • Running Reinforcement Learning Agents on GPU for Many Simulations of Two-Person Simultaneous Games. Koichi Moriyama, Yoshiya Kurogi, Atsuko Mutoh (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), and Nobuhiro Inuzuka (Nagoya Institute of Technology). Proceedings of the 4th IEEE International Conference on Agents (IEEE ICA), pp. 50-55 (2019). doi.org/10.1109/AGENTS.2019.8929206 Jinan, China, Oct. 19, 2019.
  • Safe Reinforcement Learning in Continuous State Spaces. Takumi Umemoto (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Atsuko Mutoh, Koichi Moriyama and Nobuhiro Inuzuka (Nagoya Institute of Technology). 2019 IEEE 8th Global Conference on Consumer Electronics (IEEE GCCE 2019), pp. 411-415, DOI: 10.1109/GCCE46687.2019.9014637 (2019). Osaka, Japan, Oct. 16, 2019.
  • Multi-objective safe reinforcement learning: the relationship between multi-objective reinforcement learning and safe reinforcement learning. Naoto Horie (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Koichi Moriyama, Atsuko Mutoh, Nobuhiro Inuzuka (Nagoya Institute of Technology). Artificial Life and Robotics (2019). https://doi.org/10.1007/s10015-019-00523-3 Feb. 2019.

2018

  • Accelerating Deep Q Network by Weighting Experiences. Kazuhiro Murakami, Koichi Moriyama, Atsuko Mutoh (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Nobuhiro Inuzuka (Nagoya Institute of Technology). Proceedings of the 25th International Conference on Neural Information Processing (ICONIP), Lecture Note on Computer Science, Vol. 11301, pp. 204-213, Springer (2018). https://doi.org/10.1007/978-3-030-04167-0_19 Siem Reap, Cambodia, Dec. 16, 2018.
  • Evolution Direction of Reward Appraisal in Reinforcement Learning Agents. Masaya Miyawaki, Koichi Moriyama, Atsuko Mutoh (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Nobuhiro Inuzuka (Nagoya Institute of Technology). Proceedings of the 12th International Conference on Agent & Multi-Agent Systems: Technologies & Applications (KES-AMSTA 2018), Smart Innovation, Systems and Technologies, Vol. 96, pp. 13-22, Springer, Cham (2018) https://doi.org/10.1007/978-3-319-92031-3_2 Gold Coast, Australia, Jun. 20-22, 2018.
  • Multiobjective Reinforcement Learning Using Success Probabilities and Rewards. Naoto Horie (Nagoya Institute of Technology), Tohgoroh Matsui (Chubu University), Koichi Moriyama, Atsuko Mutoh, Nobuhiro Inuzuka (Nagoya Institute of Technology). The Twenty-Third International Symposium on Artificial Life and Robotics 2018 (AROB 23rd 2018), GS12-1, pp. 246-249 (2018). Beppu, Japan, Jan. 19, 2018.

2016

2015

2013

  • Compound Reinforcement Learning: Applications of Reinforcement Learning to Finance. Tohgoroh Matsui (Chubu Univeristy). Journal of The Society of Instrument and Control Engineers, Vol. 52, No. 11, pp. 1022-1027 (2013). Nov. 2013, in Japanese.
  • Analysis of Long-term Financial Markets' Fluctuation by English Textual Information. Kiyoshi Izumi, Kyoto Yono, Chen Yu (The University of Tokyo), Takashi Goto (Tha Bank of Tokyo-Mitsubishi UFJ, Ltd.), Tohgoroh Matsui (Chubu University). JAFEE Journal, Vol. 11, pp. 12-31 (2013). Apr. 2013, in Japanese.
  • Optimizing Betting Fraction in Compound Reinforcement Learning. Tohgoroh Matsui (Chubu University), Takashi Goto (The Bank of Tokyo-Mitsubishi UFJ, Ltd.), Kiyoshi Izumi, Chen Yu (The University of Tokyo). Transactions of the Japanese Society for Artificial Intelligence, Vol. 28, No. 3, pp. 267-272 (2013). Mar. 2013, in Japanese.
  • Analysis of Long-term Market Trend by Text-Mining of News Articles. Takahisa Kuramoto, Kiyoshi Izumi, Yoshimura Shinobu (The University of Tokyo), Tomonari Ishida, Akihiro Nakashima (Nomura Securities Co., Ltd.), Tohgoroh Matsui (Chubu University), Minoru Yoshida, Hiroshi Nakagawa (The University of Tokyo). Transactions of the Japanese Society for Artificial Intelligence, Vol. 28, No. 3, pp. 291-296 (2013). Mar. 2013, in Japanese.

2012

2011

  • Compound Reinforcement Learning: Framework and Application. Tohgoroh Matsui (Chubu University), Takashi Goto (The Bank of Tokyo-Mitsubishi UFJ, Ltd.), Kiyoshi Izumi, Yu Chen (The University of Tokyo). IPSJ Journal, Vol. 52, No. 12, pp. 3300-3308 (2011). Dec. 2011, in Japanese.
  • Long-term Financial Market Analysis Using Economic Textual Information. Kiyoshi Izumi (The University of Tokyo), Takashi Goto (The Bank of Tokyo-Mitsubishi UFJ, Ltd.), Tohgoroh Matsui (Chubu University). IPSJ Journal, Vol. 52, No. 12, pp. 3309-3315 (2011). Dec. 2011, in Japanese.
  • Compound reinforcement learning. Tohgoroh Matsui. Transactions of Japanese Society for Artificial Intelligence, Vol. 26, No. 2, pp. 330-334 (2011). Jan. 2011, in Japanese.
  • Implementation tests of financial market analysis by text mining. Kiyoshi Izumi, Takashi Goto, Tohgoroh Matsui. Transactions of Japanese Society for Artificial Intelligence, Vol. 26, No. 2, pp. 313-317 (2011). Jan. 2011, in Japanese.

2010

  • Trading Tests of Long-Term Market Forecast by Text Mining. Kiyoshi Izumi, Takashi Goto, Tohgoroh Matsui. Proceedings of 2010 IEEE International Conference on Data Mining Workshops, pp. 935-942, IEEE Computer Society (2010). Sidney, Australia, Dec. 2010.
  • Analysis on financial markets' fluctuation by textual information. Kiyoshi Izumi, Takashi Goto, Tohgoroh Matsui. JSAI Magagine, Vol. 25, No. 3, pp. 383-387 (2010). May 2011, in Japanese.

2009

  • Acquiring a government bond trading strategy using reinforcement learning. Tohgoroh Matsui, Takashi Goto, Kiyoshi Izumi. Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 13, No. 6, pp. 691-696 (2009). Nov. 2009,
  • Machine learning in economic research. Kiyoshi Izumi, Toshiya Kaihara, Tohgoroh Matsui. JSAI Magazine, Vol. 24, No. 6, pp. 796-803 (2009). Nov. 2009, in Japanese.
  • Data mining from web. Tohgoroh Matsui. TUS Science Forum, Vol. 26, No. 5, pp. 29-34 (2009). May 2009, in Japanese.
  • Acquiring and analyzing trading strategy in financial market using reinforcement learning. Tohgoroh Matsui and Takashi Goto. JSAI Magazine, Vol. 24, No. 3, pp. 400-407 (2009). May 2009, in Japanese.
  • Editorial: Special Issue on AI applications in finance. Takao Terano, Tohgoroh Matsui, Kiyoshi Izumi. JSAI Magazine, Vol. 24, No. 3, pp. 373-375 (2009). May 2009, in Japanese.

2008

  • Protein Fold Prediction from Primary Structure Using Inductive Logic Programming. Tohgoroh Matsui, Hayato Ohwada, Kazuyuki Kuchitsu. Proceedings of the Workshop on Knowledge, Language, and Learning in Bioinformatics (KLLBI 2008), accepted (2008). Hanoi, Vietnam, Dec. 2008.
  • Long-Term Market Analysis Using Text Mining. Kiyoshi Izumi, Takashi Goto, Tohgoroh Matsui. Proceedings of the 7th International Conference on Computational Intelligence in Economics and Finance (CIEF 2008), accepted (2008). Taoyuan, Taiwan, Dec. 2008.
  • Artificial Market and Trading Agent Strategy. Kiyoshi Izumi, Fujio Toriumi, Tohgoroh Matsui. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol. 20, No. 4, pp. 609-615 (2008). Aug. 2008, in Japanese.
  • Artificial Intelligence: A Modern Approach (2nd Edition), Chapter 16: Making Simple Decisions (Japanese Translation). Stuart Russell, Peter Norvig (Authors), Koichi Furukawa (Translation supervisor), Hayato Ohwada, Tohgoroh Matsui (Translators). pp. 589-617, Kyoritsu Shuppan (2008). Jul. 2008, in Japanese.

2007

  • Introduction to KabuRobo: Stock trading using artificial intelligence. Tohgoroh Matsui. JSAI Magazine, Vol. 22, No. 4, pp. 540-547 (2007). Sep. 2007, in Japanese.

2006

  • Using ILP for constructing process network in dies production. Atsushi Yamazaki, Tohgoroh Matsui, Hayato Ohwada, and Kazuhiko Nakajima. The Short Papers of the 16th International Conference on Inductive Logic Programming (ILP-2006), pp. 228-230 (2006). Santiago de Compostela, Spain, Aug. 2006.

2005

  • Detecting and revising misclassifications using ILP. Masaki Yokoyama, Tohgoroh Matsui, and Hayato Ohwada. Proceedings of The 8th International Conference on Discovery Science (DS-2005), pp. 362-369 (2005). Singapore, Oct. 2005.
  • Detecting errors in POS-tagging using ILP. Masaki Yokoyama, Tohgoroh Matsui, and Hayato Ohwada. Late-Braking Papers of The 15th International Conference on Inductive Logic Programming (ILP-2005), Technical Notes TUM-I0510, pp. 75-80 (2005). Bonn, Germany, Aug. 2005.
  • Extracting common concepts from WordNet to classify documents. Yoko Ino, Tohgoroh Matsui, and Hayato Ohwada. Proceedings of The IASTED International Conference on Artificial Intelligence and Applications (AIA-2005), pp. 656-661 (2005). Innsbruck, Austria, Feb. 2005.

2004

  • Active background-knowledge selection in inductive logic programming. Hidenori Shirai, Tohgoroh Matsui, and Hayato Ohwada. Short Presentations of The 13th International Conference on Inductive Logic Programming (ILP-2003), pp. 95-104 (2003). Szeged, Hungary, Sep. 2003.
  • Predicting and revising misclassification using ILP. Toshihide Iwasaki, Tohgoroh Matsui, and Hayato Ohwada. Short Presentations of The 13th International Conference on Inductive Logic Programming (ILP-2003), pp. 22-29 (2003). Szeged, Hungary, Sep. 2003.
  • On-line profit sharing works efficiently. Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki. Proceedings of The 7th International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES 2003), Part 1, LNAI 2773, pp. 317-324, Springer-Verlag (2003). Oxford, UK, Sep. 2003.
  • Reinforcement learning methods to handle actions with differing costs in MDPs. Takahisa Ishiguro, Tohgoroh Matsui, Nobuhiro Inuzuka, and Koichi Wada. Proceedings of The 7th International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES 2003), Part 2,LNAI 2774, pp. 553-560, Springer-Verlag (2003). Oxford, UK, Sep. 2003.

2002

  • Adapting to subsequent changes of environment by learning policy preconditions. Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki. International Journal of Computer & Information Science, Vol. 3, No. 1, pp. 49-58 (2002).
  • Using concept learning for restructuring control policy in reinforcement learning. Tohgoroh Matsui, Nobuhiro Inuzuka, Hirohisa Seki, and Hidenoti Itoh. Transactions of The Japanese Society for Artificial Intelligence, Vol. 17, No. 2, pp. 135-144 (2002). Mar. 2002, in Japanese.
  • A comparison of three methods for parallelizing an ILP algorithm FOIL. Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki. The Transactions of The Institute of Electronics, Information and Communication Engineers, Vol. J85-D-I, No. 6, pp.566-568 (2002). In Japanese.
  • Feature selection for effective calculation of a similarity measure. Tomoya Ogawa, Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki. Proceedings of The IASTED International Conference on Artificial and Computational Intelligence (ACI 2002), pp. 318-323 (2002). Tokyo, Japan, Sep. 2002.

2001

  • Learning preconditions for control policies in reinforcement learning. Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki.Proceedings of The ACIS 2nd International Conference on Software Engineering, Artificial Intelligence, Networking & Parallel/Distributed Computing (SNPD '01), pp. 47-54, (2001). Nagoya, Japan, Aug. 2001.

2000

  • Adaptive behavior by inductive prediction in soccer agents. Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki.Proceedings of The 6th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2000),LNAI 1886, p. 807, Springer-Verlag (2000). Melbourne, Australia, Aug. 2000.
  • A proposal for inductive learning agent using first-order logic. Tohgoroh Matsui, Nobuhiro Inuzuka, and Hirohisa Seki. Work-in-progress reports of The 10th International Conference on Inductive Logic Programming (ILP 2000), CEUR Workshop Proceedings, Vol. 35, pp. 180-193 (2000). London, UK, Aug. 2000.

1999

  • Soccer agents learning from past behavior with inductive logic programming. Tohgoroh Matsui, Kazuo Kashiwabara, Nobuhiro Inuzuka, Hirohisa Seki, and Hidenori Itoh. Proceedings of The First IMC Workshop on Knowledge Mining in The Real-world, pp. 77-88 (1999). Tokyo, Japan, Dec. 1999.
  • An induction algorithm based on fuzzy logic programming. Daisuke Shibata, Nobuhiro Inuzuka, Shohei Kato, Tohgoroh Matsui, and Hidenori Itoh. Proceedings of The Third Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-99),LNAI 1574, pp.268-273, Springer-Verlag (1999). Beijing, China, Apr. 1999.

1998

  • Parallel induction algorithms for large samples. Tohgoroh Matsui, Nobuhiro Inuzuka, Hirohisa Seki, and Hidenori Itoh. Proceedings of The First International Conference on Discovery Science on Discovery Science (DS'98), LNAI 1532, pp.397-398, Springer-Verlag (1998). Fukuoka, Japan, Dec. 1998.
  • Comparison of three parallel implementations of an induction algorithm. Tohgoroh Matsui, Nobuhiro Inuzuka, Hirohisa Seki, and Hidenori Itoh.Proceedings of 8th International Parallel Computing Workshop (PCW'98), pp.181-188 (1998). Singapore, Sep. 1998.