(since May 7, 2012)

Last modified: August 30, 2018

This page introduces my research activities as a list of publications. Some papers are available in PDF (Portable Document Format) PDF.


Contents


Journal papers (with review):

  1. Kuremoto, T., Otani, T., Obayashi, M., Kobayashi, K., and Mabu, S., A Hand Shape Instruction Recognition and Learning System Using Growing SOM with Asymmetric Neighborhood Function, Neurocomputing, Vol.188, pp.31-41, 2016.
    Download: Full Paper (Elsevier) PDF

  2. Hirata, T., Kuremoto, T., Obayashi, M., Mabu, S., and Kobayashi, K. A Novel Approach to Time Series Forecasting using Deep Learning and Linear Model, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.136-C, No.3, pp.348-356, 2016 (in Japanese).
    Download: Full Paper (IEEJ)PDF (to appear)

  3. Kuremoto, T., Morisaki, K., Kobayashi, K., Mabu, S., and Obayashi, M., Elman Type Recurrent Neural Network with Parametric Bias and Its Application to Multi-Action Learning of Robot, ICIC Express Letters, Part B: Applications (An International Journal of Research and Surveys), Vol.6, No.9, pp.2361-2369, 2015.
    Download: Full Paper (ICIC International)PDF (to appear)

  4. Tanaka, T. and Kobayashi, K., Developing a Dividual Model Using a Modular Neural Network for Human-Robot Interaction, Journal of Robotics, Networking and Artificial Life, Vol.2, No.1, pp.34-39, 2015.
    Download: Full Paper (Atlantis) PDF

  5. Watanabe, S., Kuremoto, T., Kobayashi, K., Mabu, S., and Obayashi, M., Dynamical Recollection and Storage of Video Images via MCNN and SOM, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.135-C, No.4, pp.414-422, 2015 (in Japanese).
    Download: Full Paper (IEEJ) PDF

  6. Tsubakimoto, T. and Kobayashi, K., Cooperative Action Acquisition Based on Intention Estimation in a Multi-agent Reinforcement Learning System, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.135-C, No.1, pp.117-122, 2015 (in Japanese).
    Download: Full Paper (IEEJ) PDF

  7. Kawamura, M. and Kobayashi, K., An Action Selection Method Using Degree of Cooperation in a Multi-agent Reinforcement Learning System, Journal of Robotics, Networking and Artificial Life, Vol.1, No.3, pp.231-236, 2014.
    Download: Full Paper (Atlantis) PDF

  8. Kuremoto, T., Otani, T., Mabu, S., Obayashi, M., and Kobayashi, K., One-D-R-A-G-SOM and its Application to a Hand Shape Instruction Learning System, International Journal of Networked and Distributed Computing, Vol.2, No.3, pp.166-174, 2014.
    Download: Full Paper (Atlantis) PDF

  9. Kuremoto, T., Kimura, S., Kobayashi, K., and Obayashi, M., Time Series Forecasting Using a Deep Belief Network with Restricted Boltzmann Machines, Neurocomputing, Vol.137, pp.47-56, 2014.
    Download: Full Paper (Elsevier) PDF

  10. Uchiyama, S., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Control System Based on Auto-Fusion Cerebellar Perceptron Improved Model and Its Application to Consensus Problem, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.134-C, No.7, pp.990-998, 2014 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  11. Watada, S., Obayashi, M., Kuremoto, T., Mabu, S., and Kobayashi, K., A Decision Making System of Robots Introducing a Re-construction of Emotions Based on Their Own Experiences, Journal of Robotics, Networking and Artificial Life, Vol.1, No.1, pp.27-32, 2014
    Download: Full Paper (Atlantis) PDF

  12. Watanabe, S., Kuremoto, T., Mabu, S., Obayashi, M., and Kobayashi, K., The Recollection Characteristics of Generalized MCNN Using Different Control Methods, Journal of Robotics, Networking and Artificial Life, Vol.1, No.1, pp.73-79, 2014
    Download: Full Paper (Atlantis) PDF

  13. Watada, S., Obayashi, M., Kuremoto, T., Kobayashi, K., and Mabu, S., Behavior Selection Method of Robots Based on a Markovian Emotional Model, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.134-C, No.1, pp.85-93, 2014 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  14. Watanabe, S., Kuremoto, T., Kobayashi, K., and Obayashi, M., A Method for Analyzing the Spatiotemporal Changes of Chaotic Neural Networks, Artificial Life and Robotics, Vol.18, No.3-4, pp.196-203, 2013.
    Download: Full Paper (SpringerLink)PDF

  15. Kuremoto, T., Kinoshita, Y., Feng, L., Watanabe, S., Kobayashi, K., and Obayashi, M., A Gesture Recognition System with Retina-V1 Model and One-Pass Dynamic Programming, Neurocomputing, Vol.116, pp.291-300, 2013.
    Download: Full Paper (Elsevier)PDF

  16. Kuremoto, T., Tsurusaki, T., Kobayashi, K., Mabu, S., and Obayashi, M., An Improved Reinforcement Learning System Using Affective Factors, Robotics, Vol.2, No.3, pp.149-164, 2013.
    Download: Full Paper (Robotics)PDF

  17. Uchiyama, S., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Robust Control System Based on a Cerebellar Perceptron Model Imitating Procedural Memory, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.133-C, No.6, pp.1251-1258, 2013 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  18. Feng, L., Obayashi, M., Kuremoto, T., Kobayashi, K., and Watanabe, S., QoS Optimization for Web Service Composition Based on Reinforcement Learning, International Journal of Innovative Computing, Information and Control, Vol.9, No.6, pp.2361-2376, 2013.
    Download: Full Paper (IJICIC)PDF

  19. Kuremoto, T., Yamano, Y., Feng, L., Kobayashi, K., and Obayashi, M., Adaptive Swarm Behavior Acquisition Using a Neuro-Fuzzy Reinforcement Learning System, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.133-C, No.5, pp.1076-1085, 2013 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  20. Obayashi, M., Koga, S., Feng, L., Kuremoto, T., and Kobayashi, K., Handwriting Character Classification Using Freeman's Olfactory KIII Model, Artificial Life and Robotics, Vol.17, No.2, pp.227-232, 2012.
    Download: Full Paper (SpringerLink)PDF

  21. Uchiyama, S., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Real-time Reinforcement Learning Control System with Tracking Performance Compensator, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.132-C, No.6, pp.1008-1015, 2012 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  22. Feng, L., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Learning Fuzzy Petri Net Model, IEEJ Transactions on Electrical and Electronic Engineering, Vol.7, No.3, pp.274-282, 2012.
    Download: Full Paper (Wiley)PDF

  23. Kuremoto, T., Obayashi, M., Kobayashi, K., and Feng, L., An Improved Internal Model of Autonomous Robots by a Psychological Approach, Cognitive Computation, Vol.3, pp.501-509, 2011.
    Download: Full Paper (SpringerLink)PDF

  24. Chen, T. Y., Zhang, D., Dragomir, A., Kobayashi, K., Akay, Y., and Akay, M., Investigating the Influence of PFC Transection and Nicotine on Dynamics of AMPA and NMDA Receptors of VTA Dopaminergic Neurons, Journal of NeuroEngineering and Rehabilitation, Vol.8, No.58, doi:10.1186/1743-0003-8-58, 2011.
    Download: Full Paper (BioMed) PDF

  25. Obayashi, M., Uchiyama, S., Kuremoto, T., and Kobayashi, K., A Robust Cooperated Control Method with Reinforcement Learning and Adaptive Control, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.131-C, No.8, pp.1467-1474, 2011 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  26. Kuremoto, T., Watanabe, S., Kobayashi, K., Feng, L., and Obayashi, M., The Dynamical Recollection of Interconnected Neural Networks Using Meta-heuristics, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.131-C, No.8, pp.1475-1484, 2011 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  27. Nakano, K., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Robust Reinforcement Learning Control Design Method for Nonlinear System with Partially Unknown Structure, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.130-C, No.11, pp.2090-2091, 2010 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  28. Makino, Y., Obayashi, M., Kuremoto, T., and Kobayashi, K., Indirect Adaptive Self-structuring Fuzzy Neural Network Control System, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.130-C, No.10, pp.1882-1887, 2010 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  29. Kuremoto, T., Komoto, T., Kobayashi, K., and Obayashi, M., Parameterless-Growing-SOM and Its Application to a Voice Instruction Learning System, Journal of Robotics, Vol.2010, pp.1-9, 2010.
    Download: Full Paper (Hindawi Publishing Co.)PDF

  30. Obayashi, M., Feng, L., Kuremoto, T., and Kobayashi, K., Intelligent Agent Construction Using the Attentive Characteristic Patterns of Chaotic Neural Networks, Artificial Life and Robotics, Vol.15, No.2, pp.216-220, 2010.
    Download: Full Paper (SpringerLink)PDF

  31. Kuremoto, T., Yamano, Y., Obayashi, M., and Kobayashi, K., An Improved Internal Model for Swarm Formation and Adaptive Swarm Behavior Acquisition, Journal of Circuits, Systems, and Computers, Vol.18, No.8, pp.1517-1531, 2009.
    Download: Full Paper (World Scientific)PDF

  32. Kuremoto, T., Obayashi, M., and Kobayashi, K., Adaptive Swarm Behavior Acquisition by a Neuro-Fuzzy System and Reinforcement Learning Algorithm, International Journal of Intelligent Computing and Cybernetic, Vol.2, No.4, pp.724-744, 2009.
    Download: Full Paper (Emerald)PDF

  33. Mizoue, H., Kobayashi, K., Kuremoto, T., and Obayashi, M., A Meta-parameter Learning Method in Reinforcement Learning Based on Temporal Difference Error, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.129-C, No.9, pp.1730-1736, 2009 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  34. Kobayashi, K., Obayashi, M., and Kuremoto, T., A Local Linear Wavelet Neural Network Based on a Bayesian Design Method, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.129-C, No.7, pp.1356-1362, 2009 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  35. Kogawa, N., Obayashi, M., Kobayashi, K., and Kuremoto, T., A Reinforcement Learning Method Based on an Immune Network Adapted to a Semi-Markov Decision Process, Artificial Life and Robotics, Vol.13, No.2, pp.538-542, 2009.
    Download: Full Paper (SpringerLink)PDF

  36. Obayashi, M., Nakahara, N., Kuremoto, T., and Kobayashi, K., A Robust Reinforcement Learning Using Concept of Sliding Mode Control, Artificial Life and Robotics, Vol.13, No.2, pp.526-530, 2009.
    Download: Full Paper (SpringerLink)PDF

  37. Kuremoto, T., Ohta, T., Kobayashi, K., and Obayashi, M., A Dynamic Associative Memory System by Adopting an Amygdala Model, Artificial Life and Robotics, Vol.13, No.2, pp.478-482, 2009.
    Download: Full Paper (SpringerLink)PDF

  38. Obayashi, M., Narita, K., Kobayashi, K., and Kuremoto, T., A Transient Chaotic Associative Memory Model with Temporary Stay Function, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.128-C, No.12, pp.1852-1858, 2008 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  39. Kobayashi, K., Nakano, K., Kuremoto, T., and Obayashi, M., A State Predictor Based Reinforcement Learning System, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.128-C, No.8, pp.1303-1311, 2008 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  40. Hano, T., Kuremoto, T., Kobayashi, K., and Obayashi, M., A Hand Image Instruction Learning System Using Transient-SOM, Transactions on SICE (Society of Instrument and Control Engineering), Vol.43, No.11, pp.1004-1006, 2007 (in Japanese).
    Download: Full Paper (CiNii)PDF

  41. Kogawa, N., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Reinforcement Learning Method Based on Immune Network, Transactions on SICE (Society of Instrument and Control Engineering), Vol.43, No.6, pp.525-527, 2007 (in Japanese).
    Download: Full Paper (CiNii)PDF

  42. Obayashi, M., Omiya, R., Kuremoto, T., and Kobayashi, K., Shapes of Non-monotonous Activation Functions in Chaotic Neural Network Associative Memory Model and Its Evaluation, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.126-C, No.11, pp.1401-1405, 2006 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  43. Umesako, K., Obayashi, M., and Kobayashi, K., Evolutionary Reinforcement Learning System with Time-varying Parameters, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.124-C, No.7, pp.1478-1483, 2004 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  44. Obayashi, M., Yuda, K., Omiya, R., and Kobayashi, K., Associative Memory and Mutual Information in a Chaotic Neural Network Introducing Function Typed Synaptic Weights, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.123-C, No.9, pp.1631-1637, 2003 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  45. Umesako, K., Obayashi, M., and Kobayashi, K., Self-Organized Fuzzy Reinforcement Learning System, Transactions on SICE (Society of Instrument and Control Engineering), Vol.39, No.7, pp.699-701, 2003 (in Japanese).
    Download: Full Paper (CiNii)PDF

  46. Umesako, K., Obayashi, M., and Kobayashi, K., Reinforcement Learning Using Adaptive Search Method, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.122-C, No.3, pp.374-380, 2002 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  47. Obayashi, M., Umesako, K., and Kobayashi, K., A New Method for Faster Neural Networks Learning Introducing Functions of Synaptic Weights and Its Application to Nonlinear System Control, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.121-C, No.2, pp.385-391, 2001 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  48. Obayashi, M., Watanabe, K., and Kobayashi, K., Chaotic Neural Networks with Radial Basis Functions and Its Application to Memory Search Problem, Transactions on IEE Japan (The Institute of Electrical Engineers of Japan), Vol.120-C, No.10, pp.1441-1446, 2000 (in Japanese).
    Download: Full Paper (IEEJ)PDF

  49. Wu, B-. Y.(Kuremoto, T.), Kobayashi, K., and Torioka, T., Pattern Separating Conditions of a Layered Nerve Net ---The Number of Connections between Layers R=4---, Transactions on IEICE (The Institute of Electronics, Information and Communication Engineers), Vol.J80-D-II, No.9, pp.2573-2577, 1997 (in Japanese).
    Download: Full Paper (IEICE)PDF

  50. Ueda, N., Kobayashi, K., and Torioka, T., A Wavelet Neural Network with Evolutionally Generated Structures, Transactions on IEICE (The Institute of Electronics, Information and Communication Engineers), Vol.J80-D-II, No.2, pp.652-659, 1997 (in Japanese).
    Download: Full Paper (IEICE)PDF

  51. Kobayashi, K., Torioka, T., and Yoshida, N., A Wavelet Neural Network with Network Optimizing Function, Transactions on IEICE (The Institute of Electronics, Information and Communication Engineers), Vol.J77-D-II, No.10, pp.2121-2129, 1994 (in Japanese).
    Download: Full Paper (IEICE)PDF

  52. Kobayashi, K., Torioka, T., and Ikeda, N., Fundamental Consideration on Self-formation of Recognition Cells. Neural Networks, Vol.7, No.8, pp.1241-1252, 1994.
    Download: Full Paper (Science Direct)PDF

  53. Kobayashi, K., Hara, H., and Torioka, T., Pattern Separation Function of Two-layered Random Net with Feedforward Inhibitory Connections, Transactions on IEICE (The Institute of Electronics, Information and Communication Engineers), Vol.J77-D-II, No.3, pp.583-590, 1994 (in Japanese).
    Download: Full Paper (IEICE)PDF

Proceedings of international conferences (with review):

  1. Hirata, T., Kuremoto, T., Obayashi, M., Mabu, S., and Kobayashi, K., Deep Belief Network using Reinforcement Learning and its Applications to Time Series Forecasting, Lecture Notes in Computer Science (LNCS), Vol.9949, pp.30-37, Springer-Verlag, 2016.
    Note: this paper was also included in Proceedings of the 23th International Conference on Neural Information Processing (ICONIP2016), October 16-21, 2015 (Kyoto, Japan).
    Download: Full Paper (SpringerLink)PDF

  2. Kuremoto, T., Kuzukami, Y., Obayashi, M., Mabu, S., and Kobayashi, K., RP-AG-SOM: A Growing Self-Organizing Map with Asymmetric Neighborhood Function and Variable Radius Proceedings of SAI Intelligent Systems Conference (IntelliSys2016), pp.xx-xx, September 21-22, 2016 (London, UK) (to appear).

  3. Tanaka, T., Tsubakimoto, T., Kawamura, M., Kumagai, K., Matsubara, H., Hidaka, K., Aizawa, Y., Nakagawa, M., Iwai, Y., Suzuki, T., and Kobayashi, K., Camellia Dragons 2015 Team Description, Proceedings of the 20th Annual RoboCup International Symposium (RoboCup2016), July 4, 2016 (Leipzig, Germany).
    Download: TDP (RoboCup 2016 Symposium)PDF (to appear)

  4. Kuremoto, T., Tsubaki, K., Obayashi, M., Mabu, S., and Kobayashi, K., A Neuro-Fuzzy Reinforcement Learning System for Autonomous Robot Dealing with Continuous Space, Proceedings of International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP2016), pp.258-261, March 6-9, 2016 (Honolulu, Hawaii).

  5. Hidaka, K. and Kobayashi, K., Improvement of Computational Efficiency of {UPF} by Automatic Adjustment of the Number of Particles, Proceedings of the International Conference on Artificial Life and Robotics (ICAROB2016), pp.463-466, January 29-31, 2016 (Ginowan, Japan).

  6. Kuremoto, T., Baba, Y., Obayashi, M., Mabu, S., and Kobayashi, K., A Method of Feature Extraction for EEG Signal Recognition, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2015), pp.42-43, December 19-22, 2015 (Jiangsu, Korea).

  7. Obayashi, M., Uto, S., Kuremoto, T., Mabu, S., and Kobayashi, K., An Extended Q Learning System with Emotion State to Make up an Agent with Individuality, Proceedings of the 7th International Joint Conference on Computational Intelligence (IJCCI 2015), pp.70-78, November 12-14, 2015 (Lisbon, Portugal).

  8. Obayashi, M., Yamane, T., Kuremoto, T., Mabu, S., and Kobayashi, K., An Autonomous Mobile Robot with Functions of Action Learning, Memorizing, Recall and Identifying the Environment Using Gaussian Mixture Model, Lecture Notes in Computer Science (LNCS), Vol.9489, pp.272-282, Springer-Verlag, 2015.
    Note: this paper was also included in Proceedings of the 22th International Conference on Neural Information Processing (ICONIP2015), November 9-12, 2015 (Istanbul, Turkey).
    Download: Full Paper (SpringerLink)PDF

  9. Hirata, T., Kuremoto, T., Obayashi, M., Mabu, S., and Kobayashi, K., Time Series Prediction Using DBN and ARIMA, Proceedings of International Conference on Computer Application Technologies (CCATS2015), August 31-September 2, 2015 (Matsue, Japan).

  10. Kuremoto, T., Ko, K., Obayashi, M., Mabu, S., and Kobayashi, K., Neural Networks using Reinforcement Learning and their Applications to Time Series Forecasting, Proceedings of 3rd International Conference on Automatic Control, Soft Computing and Human-Machine Interaction (ASME2015), pp.69-74, June 27-29, 2015 (Salerno, Italy).

  11. Tsubakimoto, T., Kawamura, M., Kumagai, K., Matsubara, H., Tanaka, T., Hidaka, K., Murashima, T., and Kobayashi, K., Camellia Dragons 2015 Team Description, Proceedings of the 19th Annual RoboCup International Symposium (RoboCup2015), July 23, 2015 (Hefei, China).
    Download: TDP (RoboCup 2015 Symposium)PDF (to appear)

  12. Kuremoto, T., Baba, Y., Obayashi, M., Mabu, S., and Kobayashi, K., To Extraction the Feature of EEG Signals for Mental Task Recognition, Proceedings of International Conference on Instrumentation, Control and Information Technology (SICE Annual Conference 2015), pp.353-358, July 28-30, 2015 (Hangzhou, China).

  13. Obayashi, M., Ishikawa, K., Kuremoto, T., Mabu, S., and Kobayashi, K., Leader-Following Formation Control with an Adaptive Linear and Terminal Sliding Mode Combined Controller Using Auto-Structuring Fuzzy Neural Network, Proceedings of the Seventh International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE2015), pp.130-136, March 22-27, 2015 (Nice, France).

  14. Nunome, Y., Murakami, K., Ito, M., Kobayashi, K., and Naruse, T., A Method to Estimate Ball's State of Spin Using Co-occurrence Matrix and Inertia Feature for Strategic Positioning of Each Robot in RoboCup, Proceedings of the 2015 Joint Conference of the International Workshop on Advanced Image Technology (IWAIT) and the International Forum on Medical Imaging in Asia (IFMIA) (IWAIT2015&IFMIA2015), pp.xx-xx, January 11-13, 2015 (Tainan, Taiwan) (to appear).

  15. Tanaka, T. and Kobayashi, K., Development of a Dividual Model Using a Modular Neural Network for Human-Robot Interaction, Proceedings of the International Conference on Artificial Life and Robotics (ICAROB2015), pp.107-110, January 10-12, 2015 (Oita, Japan).

  16. Kuremoto, T., Kuzukami, Y., Obayashi, M., Kobayashi, K., and Mabu, S., A Voice Instruction Learning System using GSOM with Asymmetric Neighborhood Function, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2014), pp.72-75, December 1-3, 2014 (Jeonju, Korea).

  17. Kuremoto, T., Obayashi, M., Kobayashi, K., and Mabu, S., A Reinforcement Learning System with Neuro-Fuzzy Network and its Applications, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2014), pp.68-71, December 1-3, 2014 (Jeonju, Korea).

  18. Hirata, T., Kuremoto, T., Obayashi, M., Kobayashi, K., and Mabu, S., Time Series Prediction using DBN and ARIMAM, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2014), pp.54-57, December 1-3, 2014 (Jeonju, Korea).

  19. Kuremoto, T., Obayashi, M., Kobayashi, K., and Mabu, S., How an Adaptive Learning Rate Benefits Neuro-Fuzzy Reinforcement Learning Systems, Lecture Notes in Computer Science (LNCS), Vol.8794, pp.324-331, Springer-Verlag, 2014. Note: this paper was also included in Proceedings of the Fifth International Conference on Swarm Intelligence (ICSI2014), October 17-20, 2014 (Hefei, China).
    Download: Full Paper (SpringerLink)PDF

  20. Kuremoto, T., Hirata, T., Obayashi, M., Mabu, S., and Kobayashi, K., Forecast Chaotic Time Series Data by DBNs, Proceedings of the 7th International Congress on Image and Signal Processing (CISP2014), pp.1304-1309, October 14-16, 2014 (Dalian, China).

  21. Kuremoto, T., Morisaki, K., Kobayashi, K., Mabu, S., and Obayashi, M., A Modified Recurrent Neural Network with Parametric Bias and its Application to Action Learning of a Humanoid Robot, Proceedings of the 2nd International Conference on Intelligent Systems and Image Processing (ICISIP2014), pp.414-418, September 26-29, 2014 (Kitakyushu, Japan).

  22. Kuremoto, T., Otani, T., Obayashi, M., Kobayashi, K., and Mabu, S., A Hand Shape Instruction Recognition and Learning System Using Growing SOM with Asymmetric Neighborhood Function, Lecture Notes in Computer Science (LNCS), Vol.8588, pp.269-276, Springer-Verlag, 2014.
    Note: this paper was also included in Proceedings of the 2014 International Conference on Intelligent Computing (ICIC2014), August 3-6, 2014 (Taiyuan, China).
    Download: Full Paper (SpringerLink)PDF

  23. Kuremoto, T., Otani, T., Obayashi, M., and Kobayashi, K., Mabu, S., One Dimensional Ring Type Growing SOM with Asymmetric Neighborhood Function and its Application to a Hand Shape Instruction Learning System, Proceedings of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2014), pp.423-428, June 30 - July 2, 2014 (Las Vegas, USA).

  24. Nunome, Y., Hibino, T., Hoshino, A., Yokota, S., Adachi, Y., Ito, M., Kobayashi, K., Murakami, K., and Naruse, T., RoboDragons 2014 Team Description, Proceedings of the 19th Annual RoboCup International Symposium (RoboCup2014), July 25, 2014 (Joao Pessoa, Brazil).
    Download: TDP (RoboCup 2014 Symposium)PDF

  25. Nunome, Y., Hibino, T., Hoshino, A., Yokota, S., Adachi, Y., Ito, M., Kobayashi, K., Murakami, K., and Naruse, T., RoboDragons 2014 Extended Team Description, Proceedings of the 19th Annual RoboCup International Symposium (RoboCup2014), July 25, 2014 (Joao Pessoa, Brazil).
    Download: ETDP (RoboCup 2013 Symposium)PDF

  26. Nunome, Y., Murakami, K., Ito, M., Kobayashi, K., Murakami, K., and Naruse, T., Kobayashi, K., and Naruse, T. A Method to Estimate Ball's State of Spin by Image Processing for Improving Strategies in the RoboCup Small-Size-robot League, Lecture Notes in Artificial Intelligence (LNAI), Vol.8992, pp.514-524, Springer-Verlag, 2014 (to appear).
    Note: this paper was also included in Proceedings of the 19th Annual RoboCup International Symposium (RoboCup2014), July 25, 2014 (Joao Pessoa, Brazil).
    Download: Full Paper (SpringerLink)PDF

  27. Watada, S., Obayashi, M., Kuremoto, T., Mabu, S., and Kobayashi, K., Decision Making System of Robots introducing a Re-construction of Emotions Based on Their Own Experiences, Proceedings of the International Conference on Artificial Life and Robotics (ICAROB2014), pp.74-77, January 11-13, 2014 (Oita, Japan).

  28. Watanabe, S., Kuremoto, T., Mabu, S., Obayashi, M., and , Kobayashi, K. The Recollection Characteristics of Generalized MCNN Using Different Control Methods, Proceedings of the International Conference on Artificial Life and Robotics (ICAROB2014), pp.90-95, January 11-13, 2014 (Oita, Japan).

  29. Kawamura, M., Kobayashi, K., An Action Selection Method Using Degree of Cooperation in a Multi-agent System, Proceedings of the International Conference on Artificial Life and Robotics (ICAROB2014), pp.118-121, January 11-13, 2014 (Oita, Japan).

  30. Tsubakimoto, T. and Kobayashi, K., Cooperative Action Acquisition Based on Intention Estimation Method in a Multi-agent Reinforcement Learning System, Proceedings of the International Conference on Artificial Life and Robotics (ICAROB2014), pp.122-125, January 11-13, 2014 (Oita, Japan).

  31. Nunome, Y., Murakami, K., Ito, M., Kobayashi, K., and Naruse, T., A Method to Estimate Ball's State of Spin by Image Processing for Strategic Learning in RoboCup Small-Size-robot League, Proceedings of the International Workshop on Advanced Image Technology (IWAIT2014), pp.xx-xx, January 6-8, 2014 (Bangkok, Thailand) (to appear).

  32. Watanabe, S., Kuremoto, T., Kobayashi, K., Mabu, S., and Obayashi, M., The Recollection Characteristics of Generalized MCNN Using Different Control Methods, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2013), pp.66-69, December 3-4, 2013 (Dalian, China).

  33. Kuremoto, T., Watanabe, S., Kobayashi, K., Mabu, S., and Obayashi, M., Innovative Practice of Robotics Education using LEGO Mindstorm NXT, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2013), pp.74-77, December 3-4, 2013 (Dalian, China).

  34. Obayashi, M., Shinkawa, M., Kuremoto, T., Kobayashi, K., and Mabu, S., An Innovative Mental Task Classification Method with a Hierarchical Structure Based on EEG Data, Proceedings of International Conference on Innovative Application Research and Education (ICIARE2013), pp.92-95, December 3-4, 2013 (Dalian, China).

  35. Obayashi, M., Kamikariya, T., Uchiyama, S., Watada, S., Kuremoto, T., Mabu, S., and Kobayashi, K., Adaptive Control System Based on Self-organizing Wavelet Neural Network with Tracking Performance Compensator, Proceedings of International Conference on Systems, Man and Cybernetics (SMC2013), pp.3232-3237, October 13-16, 2013 (Manchester, U.K.).
    Download: Full Paper (IEEE Xplore)PDF

  36. Watanabe, S., Kuremoto, T., Kobayashi, K., Mabu, S., and Obayashi, M., The Recollection Characteristics of a Generalized MCNN, Proceedings of International Conference on Instrumentation, Control and Information Technology (SICE Annual Conference 2013), pp.1375-1380, September 14-17, 2013 (Nagoya, Japan).

  37. Kuremoto, T., Tsurusaki, T., Kobayashi, K., Mabu, S., and Obayashi, M., A Model of Emotional Intelligent Agent for Cooperative Goal Exploration, Lecture Notes in Computer Science (LNCS), Vol.7995, pp.21-30, Springer-Verlag, 2013.
    Note: this paper was also included in Proceedings of the 2013 International Conference on Intelligent Computing (ICIC2013), July 28-31, 2013 (Nanning, China).
    Download: Full Paper (SpringerLink)PDF

  38. Obayashi, M. Otomi, Y., Kuremoto, T., Kobayashi, K., and Mabu, S., Decentralized Adaptive Control Using an Affine plus Self-organizing Fuzzy Neural Network for Multi-Agent System Consensus Problem, Proceedings of the IEEE International Conference on System Science and Engineering (ICSSE2013), pp.247-252, July 4-6, 2013 (Budapest, Hungary).
    Download: Full Paper (IEEE Xplore)PDF

  39. Yasui, K., Kobayashi, K., Murakami, K., and Naruse, T., Analyzing and Learning Opponent's Strategies in the RoboCup Small Size League, Lecture Notes in Artificial Intelligence (LNAI), Vol.8371, pp.159-170, Springer-Verlag, 2014.
    Note: this paper was also included in Proceedings of the 17th Annual RoboCup International Symposium (RoboCup2013)
    , July 1, 2013 (Eindhoven, The Netherlands).
    Download: Full Paper (SpringerLink)PDF

  40. Yasui, K., Nunome, Y., Matsuoka, S., Adachi, Y., Atomi, K., Ito, M., Kobayashi, K., Murakami, K., and Naruse, T., RoboDragons 2013 Team Description, Proceedings of the 17th Annual RoboCup International Symposium (RoboCup2013), July 1, 2013 (Eindhoven, The Netherlands).
    Download: TDP (RoboCup 2014 Symposium)PDF

  41. Yasui, K., Nunome, Y., Matsuoka, S., Adachi, Y., Atomi, K., Ito, M., Kobayashi, K., Murakami, K., and Naruse, T., RoboDragons 2013 Extended Team Description, Proceedings of the 17th Annual RoboCup International Symposium (RoboCup2013), July 1, 2013 (Eindhoven, The Netherlands).
    Download: ETDP (RoboCup 2013 Symposium)PDF

  42. Watada, S., Obayashi, M., Kuremoto, T., Kobayashi, K., and Mabu, S., A New Decision-Making System of an Agent Based on Emotional Model in Multi Agent System, Proceedings of the 18th International Symposium on Artificial Life and Robotics (AROB2013), pp.452-455, January 30-February 1, 2013 (Daejeon, Korea).

  43. Watanabe, S., Kuremoto, T., Kobayashi, K., and Obayashi, M., The Effect of the Internal Parameters on Association Performance of a Chaotic Neural Network, Proceedings of the 18th International Symposium on Artificial Life and Robotics (AROB2013), pp.464-467, January 30-February 1, 2013 (Daejeon, Korea).

  44. Kuremoto, T., Hashiguchi, K., Morisaki, K., Watanabe, S., Kobayashi, K., Mabu, S., and Obayashi, M., Multiple Action Sequence Learning and Automatic Generation for a Humanoid Robot Using RNNPB and Reinforcement Learning, A Journal of Software Engineering and Applications, Vol.5, pp.128-133, 2012.
    Note: this paper was also included in Proceedings of the 2012 Conference on Computer Science and Software Engineering (CSSE2012)
    , December 29-31, 2012 (Sanya, China).
    Download: Full Paper (Scientific Research)PDF

  45. Kobayashi, K., Kurano, T., Kuremoto, T., and Obayashi, M., Cooperative Behavior Acquisition in Multi-agent Reinforcement Learning System Using Attention Degree, Lecture Notes in Computer Science (LNCS), Vol.7665, pp.537-544, Springer-Verlag, 2012.
    Note: this paper was also included in Proceedings of 19th International Conference on Neural Information Processing (ICONIP2012), November 12-15, 2012 (Doha, Qatar).
    Download: Full Paper (SpringerLink)PDF or ICONIP12.pdfPDF

  46. Obayashi, M., Takuno, T., Kuremoto, T., and Kobayashi, K., An Emotional Model Embedded Reinforcement Learning System, Proceedings of International Conference on Systems, Man and Cybernetics (SMC2012), pp.1058-1063, October 14-17, 2012 (Seoul, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  47. Kuremoto, T., Otani, T., Feng, L., Kobayashi, K., and Obayashi, M., A Hand Image Instruction Learning System Using PL-G-SOM, Proceedings of the 2012 International Conference on Artificial Intelligence (ICAI2012), pp.636-642, July 16-19, 2012 (Las Vegas, USA).
    Download: Full Paper (ICAI2012)PDF

  48. Kuremoto, T., Kimura, S., Kobayashi, K., and ,Obayashi, M., Time Series Forecasting Using Restricted Boltzmann Machine, Communications in Computer and Information Science (CCIS), Vol.304, pp.17-22, Springer-Verlag, 2012.
    Note: this paper was also included in Proceedings of the 2012 International Conference on Intelligent Computing (ICIC2012), July 25-29, 2012 (Huangshan, China).
    Download: Full Paper (SpringerLink)PDF

  49. Obayashi, M., Koga, S., Kuremoto, T., and Kobayashi, K., Handwriting Character Classification Using Freeman's Olfactory KIII Model, Proceedings of the 17th International Symposium on Artificial Life and Robotics (AROB2012), pp.1040-1043, January 19-21, 2012 (Beppu, Japan).

  50. Obayashi, M., Watanabe, K., Kuremoto, T., and Kobayashi, K., Development of a Brain Computer Interface Using Inexpensive Commercial EEG Sensor with One-channel, Proceedings of the 17th International Symposium on Artificial Life and Robotics (AROB2012), pp.714-717, January 19-21, 2012 (Beppu, Japan).

  51. Feng, L., Obayashi, M., Kuremoto, T., and Kobayashi, K., Optimization and Verification for a Robot Control System Based on Learning Petri Net Model, Lecture Notes in Electrical Engineering (LNEE), Vol.133, pp.815-823, Springer-Verlag, 2011.
    Note: this paper was also included in Proceedings of the 3rd International Asia Conference on Informatics in Control, Automation and Robotics (CAR2011), December 24-25, 2011 (Shenzhen, China).
    Download: Full Paper (SpringerLink)PDF

  52. Kuremoto, T., Yamano, Y., Feng, L., Kobayashi, K., and Obayashi, M., A Neuro-Fuzzy Network with Reinforcement Learning Algorithms for Swarm Learning, Lecture Notes in Electrical Engineering (LNEE), Vol.144, pp.101-108, Springer-Verlag, 2011.
    Note: this paper was also included in Proceedings of 2011 International Conference on Future Wireless Networks and Information Systems (ICFWI2011), November 30-December 1, 2011 (Macao, China).
    Download: Full Paper (SpringerLink)PDF

  53. Uchiyama, S., Obayashi, M., Kuremoto, T., and Kobayashi, K., Robust Reinforcement Learning Control System with Auto-Structuring Fuzzy Neural Network, Proceedings of the 3rd International Symposium on Digital Manufacturing 2011 (ISDM2011), pp.95-100, November 30-December 2, 2011 (Kitakyushu, Japan).

  54. Kobayashi, K., Kanehira, R., Kuremoto, T., and Obayashi, M., An Action Selection Method Based on Estimation of Other's Intention in Time-Varying Multi-Agent Environments, Lecture Notes in Computer Science (LNCS), Vol.7064, pp.76-85, Springer-Verlag, 2011.
    Note: this paper was also included in Proceedings of 18th International Conference on Neural Information Processing (ICONIP2011), November 14-17, 2011 (Shanghai, China).
    Download: Full Paper (SpringerLink)PDF or ICONIP11.pdfPDF

  55. Obayashi, M., Yokoji, Y., Uchiyama, S., Feng, L., Kuremoto, T., and Kobayashi, K., Intelligent Tracking Control Method of a Target by Group of Agents with Nonlinear Dynamics, Proceedings of International Conference on Control, Automation and Systems (ICCAS2011), pp.928-933, October 26-29, 2011 (Gyeonggi-do, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  56. Uchiyama, S., Obayashi, M., Kuremoto, T., and Kobayashi, K., Robust Reinforcement Learning Control System with Tracking Performance Compensator, Proceedings of International Conference on Control, Automation and Systems (ICCAS2011), pp.248-253, October 26-29, 2011 (Gyeonggi-do, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  57. Kuremoto, T., Kinoshita, Y., Feng, L., Watanabe, S., Kobayashi, K., and ,Obayashi, M., A Gesture Recognition System Using One-Pass DP Method, Lecture Notes in Artificial Intelligence (LNAI), Vol.6839, pp.581-587, Springer-Verlag, 2011.
    Note: this paper was also included in Proceedings of the 2011 International Conference on Intelligent Computing (ICIC2011), August 11-14, 2011 (Zhengzhou, China).
    Download: Full Paper (SpringerLink)PDF

  58. Kuremoto, T., Yamane, T., Feng, L., Kobayashi, K., and ,Obayashi, M., A Human-Machine Interaction System: A Voice Command Learning System Using PL-G-SOM, Proceedings of 2011 International Conference on Industrial Engineering and Management (IEM2011), Vol.2, pp.83-86, August 12-14, 2011 (Zhengzhou, China).
    Download: Full Paper (IEEE Xplore)PDF

  59. Obayashi, M., Nishida, T., Kuremoto, T., Kobayashi, K., and Feng, L., A Reinforcement Learning System Embedded Agent with Neural Network-Based Multi-valued Pattern Memory Structure, Proceedings of International Conference on Control, Automation and Systems (ICCAS2010), pp.176-181, October 27-30, 2010 (Gyeonggi-do, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  60. Feng, L., Obayashi, M., Kuremoto, T., and Kobayashi, K., An Intelligent Control System Construction Using High-level Time Petri Net and Reinforcement Learning, Proceedings of International Conference on Control, Automation and Systems (ICCAS2010), pp.535-539, October 27-30, 2010 (Gyeonggi-do, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  61. Kuremoto, T., Obayashi, M., Kobayashi, K., and Feng, L., Autonomic Behaviors of Swarm Robots Driven by Emotion and Curiosity, Lecture Notes in Bioinformatics (LNBI), Vol.6330, pp.541-547, Springer-Verlag, 2010.
    Note: this paper was also included in Proceedings of 2010 International Conference on Life System Modeling and Simulation & 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment (LSMS & ICSEE2010), September 17-20, 2010 (Wuxi, China).
    Download: Full Paper (SpringerLink)PDF

  62. Feng, L., Obayashi, M., Kuremoto, T., and Kobayashi, K., A Learning Petri Net Model Based on Reinforcement Learning, Proceedings of the 15th International Symposium on Artificial Life and Robotics (AROB2010), pp.290-293, February 4-6, 2010 (Beppu, Japan).

  63. Obayashi, M., Kuremoto, T., and Kobayashi, K., Intelligent Agent Construction Using the Attentive Characteristic Patterns of Chaotic Neural Networks, Proceedings of the 15th International Symposium on Artificial Life and Robotics (AROB2010), pp.597-600, February 4-6, 2010 (Beppu, Japan).

  64. Kobayashi, K., Mizoue, H., Kuremoto, T., and Obayashi, M., A Meta-learning Method Based on Temporal Difference Error, Lecture Notes in Computer Science (LNCS), Vol.5863, pp.530-537, Springer-Verlag, 2009.
    Note: this paper was also included in Proceedings of 16th International Conference on Neural Information Processing (ICONIP2009), pp.373-374, December 1-5, 2009 (Bangkok, Thailand).
    Download: Full Paper (SpringerLink)PDF or ICONIP09.pdfPDF

  65. Obayashi, M., Yamada, K., Kuremoto, T., and Kobayashi, K., A Robust Reinforcement Learning System Using Sliding Mode Control with State Variable Filters, Proceedings of 2009 CACS (Chinese Automatic Control Society) International Automatic Control Conference (CACS2009), CD-ROM, November 27-29, 2009 (Taipei, Taiwan).

  66. Kuremoto, T., Ohta, T., Kobayashi, K., and Obayashi, M., A Functional Model of Limbic System of Brain, Lecture Notes in Computer Science (LNCS), Vol.5819, pp.135-146, Springer-Verlag, 2009.
    Note: this paper was also included in Proceedings of 2009 International Conference on Brain Informatics (BI2009), October 22-24, 2009 (Beijing, China).
    Download: Full Paper (SpringerLink)PDF

  67. Kuremoto, T., Komoto, T., Kobayashi, K., and Obayashi, M., A Voice Instruction Learning System Using PL-T-SOM, Proceedings of the 2nd International Conference on Image and Signal Processing (CISP2009), pp.1-6, October 17-19, 2009 (Tianjin, China).
    Download: Full Paper (IEEE Xplore)PDF

  68. Obayashi, M., Kuremoto, T., and Kobayashi, K., A Self-Organized Fuzzy-Neuro Reinforcement Learning System for Continuous State Space for Autonomous Robots, Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA08), pp.551-556, December 10-12, 2008 (Vienna, Austria).
    Download: Full Paper (IEEE Xplore)PDF

  69. Kobayashi, K., Obayashi, M., and Kuremoto, T., A Bayesian Local Linear Wavelet Neural Network, Lecture Notes in Computer Science (LNCS), Vol.5507, pp.147-154, Springer-Verlag, 2009.
    Note: this paper was also included in Proceedings of 15th International Conference on Neural Information Processing (ICONIP2008), pp.113-114, November 25-28, 2008 (Auckland, New Zealand).
    Download: Full Paper (SpringerLink)PDF or ICONIP08.pdfPDF

  70. Obayashi, M., Narita, K., Kuremoto, T., and Kobayashi, K., A Reinforcement Learning System with Chaotic Neural Networks-Based Adaptive Hierarchical Memory Structure for Autonomous Robots, Proceedings of International Conference on Control, Automation and Systems (ICCAS2008), pp.69-74, October 14-17, 2008 (Seoul, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  71. Kuremoto, T., Obayashi, M., Kobayashi, K.., Adachi, H., and Yoneda, K., A Neuro-fuzzy Learning System for Adaptive Swarm Behaviors Dealing with Continuous State Space, Lecture Notes in Computer Science (LNCS), Vol.5227, pp.675-683, Springer-Verlag, 2008.
    Note: this paper was also included in Proceedings of the 2008 International Conference on Intelligent Computing (ICIC2008), September 15-18, 2008 (Shanghai, China).
    Download: Full Paper (SpringerLink)PDF

  72. Kuremoto, T., Obayashi, M., Kobayashi, K., Adachi, H., and Yoneda, K., A Reinforcement Learning System for Swarm Behaviors, Proceedings of the 2008 IEEE World Congress on Computational Intelligence (WCCI2008), pp.3711-3716, June 1-6, 2008 (Hong Kong, China).
    Download: Full Paper (IEEE Xplore)PDF

  73. Kuremoto, T., Ohta, T., Kobayashi, K., and Obayashi, M., A Dynamic Associative Memory System Adopting Amygdala Model, Proceedings of the 13th International Symposium on Artificial Life and Robotics (AROB2008), pp.563-566, January 31-February 2, 2008 (Beppu, Japan).

  74. Obayashi, M., Yano, Y., Kobayashi, K., and Kuremoto, T., Chaotic Dynamical Associative Memory Model Using Supervised Learning, Proceedings of the 13th International Symposium on Artificial Life and Robotics (AROB2008), pp.555-558, January 31-February 2, 2008 (Beppu, Japan).

  75. Obayashi, M., Nakahara, N., Kuremoto, T., and Kobayashi, K., A Robust Reinforcement Learning Using Concept of Sliding Mode Control, Proceedings of the 13th International Symposium on Artificial Life and Robotics (AROB2008), pp.547-550, January 31-February 2, 2008 (Beppu, Japan).

  76. Kogawa, N., Obayashi, M., Kobayashi, K., and Kuremoto, T., A Reinforcement Learning Method Based on Immune Network Adapted to Semi Markov Decision Process, Proceedings of the 13th International Symposium on Artificial Life and Robotics (AROB2008), pp.63-66, January 31-February 2, 2008 (Beppu, Japan).

  77. Kobayashi, K., Nakano, K., Kuremoto, T., and Obayashi, M., Cooperative Behavior Acquisition of Multiple Autonomous Mobile Robots by an Objective-based Reinforcement Learning System, Proceedings of International Conference on Control, Automation and Systems (ICCAS2007), pp.777-780, October 17-20, 2007 (Seoul, Korea).
    Download: ICCAS07.pdfPDF

  78. Kuremoto, T., Hano, T., Kobayashi, K., and Obayashi, M., Robot Feeling Formation Based on Image Features, Proceedings of International Conference on Control, Automation and Systems (ICCAS2007), pp.758-761, October 17-20, 2007 (Seoul, Korea).
    Download: Full Paper (IEEE Xplore)PDF

  79. Kuremoto, T., Obayashi, M., and Kobayashi, K., Forecasting Time Series by SOFNN with Reinforcement Learning, Proceedings of the 27th Annual International Symposium on Forecasting (ISF2007), pp.99, June 24-27, 2007 (New York, USA).
    Download: Full Paper (ISF2007)PDF

  80. Obayashi, M., Kogawa, N., Toyota, S., Kobayashi, K., Kuremoto, T., Controller Design Based on Immune Concept and Its Application to Chaotic Control, Proceedings of 2006 CACS Automatic Control Conference (CACS2006), pp.327-331, November 10-11, 2006 (Tamsui, Taiwan).

  81. Kuremoto, T., Hano, T., Kobayashi, K., and Obayashi, M., For Partner Robots: A Hand Instruction Learning System Using Transient-SOM, Proceedings of the 2nd International Conference on Natural Computation and the 3rd International Conference on Fuzzy Systems and Knowledge (ICNC-FSKD2006), pp.403-414, September 24-28, 2006 (Xi'an, China).

  82. Kogawa, N., Obayashi, M., Kobayashi, K., and Kuremoto, T., Learning Method of Cooperative Team Play Using the Immune System, Proceedings of the 11th International Symposium on Artificial Life and Robotics (AROB2006), pp.183-186, pp.183-186, January 23-25, 2006 (Beppu, Japan).

  83. Kuremoto, T., Eto, T., Kobayashi, K., and Obayashi, M., A Chaotic Model of Hippocampus-Neocortex, Lecture Notes in Computer Science (LNCS), Vol.3610, pp.439-448, Springer-Verlag, 2005.
    Note: this paper was also included in Proceedings of the 1st International Conference on Natural Computation (ICNC2005), August 27-29, 2005 (Changsha, China).
    Download: Full Paper (SpringerLink)PDF

  84. Kuremoto, T., Obayashi, M., and Kobayashi, K., Nonlinear Prediction by Reinforcement Learning, Lecture Notes in Computer Science (LNCS), Vol.3644, pp.1085-1094, Springer-Verlag, 2005.
    Note: this paper was also included in Proceedings of the International Conference on Intelligent Computing (ICIC2005), August 23-26, 2005 (Hefei, China).
    Download: Full Paper (SpringerLink)PDF

  85. Kobayashi, K., Mizuno, S., Kuremoto, T., and Obayashi, M., A Reinforcement Learning System Based on State Space Construction Using Fuzzy ART, Proceedings of International Conference on Instrumentation, Control and Information Technology (SICE Annual Conference 2005), pp.3653-3658, August 8-10, 2005 (Okayama, Japan).
    Download: SICE05.pdfPDF

  86. Kuremoto, T., Eto, T., Kobayashi, K., and Obayashi, M., A Multi-layered Chaotic Neural Network for Associative Memory, Proceedings of International Conference on Instrumentation, Control and Information Technology (SICE Annual Conference 2005), pp.1020-1023, August 8-10, 2005 (Okayama, Japan).

  87. Nakano, K., Obayashi, M., Kobayashi, K., and Kuremoto, T., Cooperative Behavior Acquisition for Multiple Autonomous Mobile Robots, Proceedings of the 10th International Symposium on Artificial Life and Robotics (AROB2005), pp.543-546, February 4-6, 2005 (Beppu, Japan).

  88. Kogawa, N., Obayashi, M., Maeda, A., Kobayashi, K., and Kuremoto, T., Construction and Strategy of a Soccer Team by the Agent Using Immune Concept, Proceedings of the 10th International Symposium on Artificial Life and Robotics (AROB2005), pp.342-345, February 4-6, 2005 (Beppu, Japan).

  89. Kuremoto, T., Koga, K., Kobayashi, K., and Obayashi, M., Computing Slow Optical Flow by Interpolated Quadratic Surface Matching, Proceedings of the 4th IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP2004), pp.346-351, September 6-8, 2004 (Marbella, Spain).

  90. Kuremoto, T., Obayashi, M., Yamamoto, A., and Kobayashi, K., Predicting Chaotic Time Series by Reinforcement Learning, Proceedings of the 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems (CIRAS2003), CD-ROM, December 15-18, 2003 (Singapore).

  91. Kuremoto, T., Obayashi, M., Yamamoto, A., and Kobayashi, K., Neural Prediction of Chaotic Time Series Using Stochastic Gradient Ascent Algorithm, Proceedings of the 35th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS03), pp.17-22, October 30-31, 2003 (Ube, Yamaguchi).

  92. Obayashi, M., Oda, T., Kobayashi, K., Kuremoto, T., and Kitano, H., Reinforcement Learning System with Time Varying Parameters Using Neural Network, Proceedings of the 35th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS03), pp.11-16 , October 30-31, 2003 (Ube, Yamaguchi).

  93. Umesako, K., Obayashi, M., and Kobayashi, K., Evolutionary and Time-varying Reinforcement Learning System Based on Overlap of Rules, Proceedings of 6th Japan-France Congress and 4th Asia-Europe Congress on Mechatronics (JFM2003), pp.202-207, September 9-12, 2003 (Hatoyama, Saitama).

  94. Umesako, K., Obayashi, M., and Kobayashi, K., Evolutionary and Time-Varying Reinforcement Learning System for Unobservable Dynamic Environment, Proceedings of the Eighth International Symposium on Artificial Life and Robotics (AROB2003), pp.82-85, January 24-26, 2003 (Oita, Japan).

  95. Umesako, K., Obayashi, M., and Kobayashi, K., Evolutionary Reinforcement Learning System with Time-Varying Parameters, Proceedings of the International Conference on Control, Automation and Systems (ICCAS2002), pp.1284-1287, October 16-19, 2002 (Jeonbuk, Korea).

  96. Kobayashi, K., Watanabe, K., and Obayashi, M., A Chaotic Memory Search Model Based on Associative Dynamics Using Features in Stored Patterns, Proceedings of 41st Society of Instrument and Control Engineering Annual Conference (SICE2002), pp.2919-2924, August 5-7, 2002 (Osaka, Japan).
    Download: SICE02.pdfPDF

  97. Umesako, K., Obayashi, M., and Kobayashi, K., Fast Reinforcement Learning Using Asymmetric Probability Density Function, Proceedings of 41st Society of Instrument and Control Engineering Annual Conference (SICE2002), pp.907-912, August 5-7, 2002 (Osaka, Japan).

  98. Umesako, K., Obayashi, M., and Kobayashi, K., Mobile Robot Control Using Self-Organized Fuzzy Reinforcement Learning System, Proceedings of International Symposium on Advanced Control of Industrial Processes (AdCONIP2002), pp.513-519, June 10-11, 2002 (Kumamoto, Japan).

  99. Obayashi, M., Yuda, K., Watanabe, K., and Kobayashi, K., Evaluation of Three Types Input-Output Functions of Chaotic Neural Network in Memory Search Problem, Proceedings of 7th International Conference on Neural Information Processing (ICONIP2000), pp.1130-1135, November 14-18, 2000 (Taejon, Korea).

  100. Watanabe, K., Obayashi, M., and Kobayashi, K., Memory Search Using Chaotic Neural Network with Feature Dynamics, Proceedings of 7th International Conference on Neural Information Processing (ICONIP2000), pp.1124-1129, November 14-18, 2000 (Taejon, Korea).

  101. Nagashima, T., Kobayashi, K., and Obayashi, M., An Effective Solution to Large-scale Traveling Salesman Problems Using Chaotic Neural Networks, Proceedings of 7th International Conference on Neural Information Processing (ICONIP2000), pp.459-464, November 14-18, 2000 (Taejon, Korea).
    Download:
    ICONIP00.pdfPDF

  102. Umesako, K., Obayashi, M., and Kobayashi, K., Reinforcement Learning for Dynamic System in Incomplete Observation Environment, Proceedings of 7th International Conference on Neural Information Processing (ICONIP2000), pp.434-439, November 14-18, 2000 (Taejon, Korea).

  103. Obayashi, M. and Kobayashi, K., A New Method for Faster Neural Networks Learning Introducing Functions of Synaptic Weights, Proceedings of International Conference on Neural Information Processing (ICONIP1999), Vol.3, pp.1178-1183, November 16-20, 1999 (Perth, Australia).

  104. Obayashi, M. and Kobayashi, K., Neural Networks with Functions of Synaptic Weights and Its Application to Nonlinear System Control, Proceedings of International Conference on Systems, Man and Cybernetics (SMC1999), Vol.1, pp.472-477, October 12-15, 1999 (Tokyo, Japan).

  105. Kobayashi, K. and Ohbayashi, M., A New Indirect Encoding Method with Variable Length Gene Code to Optimize Neural Network Structures, Proceedings of 1999 International Joint Conference on Neural Networks (IJCNN1999), Vol.6, pp.4409-4412, July 10-16, 1999 (Washington D.C., USA).
    Download:
    IJCNN99.pdfPDF

  106. Kobayashi, K.Introducing a Clustering Technique into Recurrent Neural Networks for Solving Large-scale Traveling Salesman Problems, Proceedings of the 8th International Conference on Artificial Neural Networks (ICANN1998), Vol.2, pp.935-940, Springer Verlag, September 2-4, 1998 (Skovde, Sweden).
    Download: ICANN98.pdfPDF

  107. Kobayashi, K. and Torioka, T., Designing Wavelet Networks Using Genetic Algorithms, Proceedings of 5th European Congress on Intelligent Techniques and Soft Computing (EUFIT1997), Vol.1, pp.429-433, Verlag Mainz, September 8-12, 1997 (Aachen, Germany).
    Download:
    EUFIT97.pdfPDF

  108. Kobayashi, K. and Torioka, T., A Wavelet Neural Network for Function Approximation and Network Optimization, Proceedings of Artificial Neural Networks In Engineering (ANNIE1994), Vol.4, pp.505-510, AMSE Press, November 13-16, 1994 (St. Louis, USA).
    Note: this paper was awarded as "Best Theoretical Development" at the conference. The citation is here.
    Download: ANNIE94.pdf (117KB)PDF

Books:

  1. Obayashi, M., Kuremoto, T., and Kobayashi, K., Intelligent Computing, Yamaguchi University, 2010 (in Japanese).

  2. Uchimura, S. and Kobayashi, K., A Textbook of Design & Engineering Practice I&II, Yamaguchi University, 2009 (in Japanese) [ISBN: 978-4-902207-04-4].

  3. Yamaguchi, S., Saeki, T., Kobayashi, K., Miyajima, K., and Koga, K., A Textbook of Information Engineering Experiment and Exercise II, Yamaguchi University, 2002 (in Japanese) [ISBN: 978-4-902207-00-1].

Chapter in books:

  1. Kuremoto, T., Obayashi, M., Mabu, S., and Kobayashi, K. Mental Task Recognition by EEG Signals: A Novel Approach with ROC Analysis, Human-Robot Interaction - Theory and Application (ed. Gholamreza Anbarjafari), Chapter 4, pp.65-78, InTech Publishing (Vienna, Austria), 2016 [ISBN: 978-1-62417-413-1]
    Download: Full Chapter (InTech Publishing)PDF

  2. Obayashi, M., Uto, M., Kuremoto, T., Mabu, S., and Kobayashi, K. An Emotional Robot, Computational Intelligence (ed. Juan Julián Merelo et al.), pp.423-443, Springer Nature Switzerland AG (Switzerland ), 2016 [ISBN 978-3-319-48506-5]
    Download: Full Chapter (Springer)PDF

  3. Kobayashi, K., A Novel Development of Human-Robot Interaction, Application of Machine Learning to Service-Oriented Systems (ed. Research Committee on Machine Learning for Optimization and Streamline of Service-Oriented Systems), Chapter 2, pp.17-23, IEEJ (Tokyo, Japan), 2015 (in Japanese).
    Download: Full Chapter (IEEJ)PDF

  4. Kuremoto, T., Obayashi, M., Kobayashi, K. Neuro-Fuzzy Systems for Autonomous Mobile Robots, Horizons in Computer Science Research (ed. Thomas S. Clary), Vol. 8, Chapter 3, pp.67-90, Nova Science Publishers, Inc. (New York, USA), 2013 [ISBN: 978-1-62417-413-1]
    Download: Full Chapter (Nova Science)PDF

  5. Kuremoto, T., Kobayashi, K., and Obayashi, M., Instruction Learning Systems for Partner Robots, Advances in Robotics - Modeling, Control and Applications (ed. Calin Ciufudean and Lino Garcia), Chapter 12, pp.197-214, iConcept Press (Queensland, Australia), 2013 [ISBN: 978-14611084-4-3].
    Download: Full Chapter (iConcept)PDF

  6. Kobayashi, K., Intention Estimation and Action Prediction in a Multi-agent System, Fundamentals and Applications of Recent Machine Learning (ed. Research Committee on Real Application Oriented Machine Learning), Chapter 3.4, pp.15-19, IEEJ (Tokyo, Japan), 2013 (in Japanese).
    Download: Full Chapter (IEEJ)PDF

  7. Kuremoto, T., Obayashi, M., and Kobayashi, K., A Chaotic Memory System Accelerated by an Emotional Model, Insights into the Amygdala: Structure, Functions and Implications for Disorders (ed. Deniz Yilmazer-Hanke), Chapter 9, pp.229-254, Nova Science Publishers, Inc. (New York, USA), 2012 [ISBN: 978-1-62257-011-9].
    Download: Full Chapter (Nova Science)PDF

  8. Feng, L., Obayashi, M., Kuremoto, T., and Kobayashi, K., Construction and Application of Learning Petri Net, Petri Nets - Manufacturing and Computer Science (ed. Pawel Pawlewski), Chapter 7, pp.143-176, InTech Publishing (Vienna, Austria), 2012 [ISBN 978-953-51-0700-2].
    Download: Full Chapter (INTECH)PDF

  9. Obayashi, M., Nakahara, N., Yamada, K., Kuremoto, T., Kobayashi, K., and Feng, L., A Robust Reinforcement Learning System Using Concept of Sliding Mode Control with State Variable Filters for Unknown Nonlinear Dynamical System, Robust Control, Theory and Applications (ed. Andrzej Bartoszewicz), Chapter 9, pp.197-214, InTech Publishing (Vienna, Austria), 2011 [ISBN: 978-953-307-229-6].
    Download: Full Chapter (INTECH)PDF

  10. Obayashi, M., Narita, K., Okamoto, Y., Kuremoto, T., Kobayashi, K., and Feng, L., A Reinforcement Learning System Embedded Agent with Neural Network-Based Adaptive Hierarchical Memory Structure, Advances in Reinforcement Learning (ed. Abdelhamid Mellou), Chapter 11, pp.189-208, InTech Publishing (Vienna, Austria), 2011 [ISBN: 978-953-307-369-9].
    Download: Full Chapter (INTECH)PDF

  11. Kobayashi, K., Nakano, K., Kuremoto, T., and Obayashi, M., Objective-based Reinforcement Learning System for Cooperative Behavior Acquisition, Application of Machine Learning (ed. Yagang Zhang), Chapter 14, pp.233-244, InTech Publishing (Vienna, Austria), 2010 [ISBN: 978-953-307-035-3].
    Download: Full Chapter (INTECH)PDF

  12. Kuremoto, T., Obayashi, M., and Kobayashi, K., Neural Forecasting Systems, Reinforcement Learning, Theory and Application (ed. Cornelius Weber, Mark Elshaw and Norbert Michael Mayer), Chapter 1, pp.1-20, InTech Publishing (Vienna, Austria), 2008 [ISBN: 978-3-902613-14-1].
    Download: Full Chapter (I-Tech)PDF

  13. Kuremoto, T., Eto, T., Kobayashi, K., and Obayashi, M., A Hippocampus-Neocortex Model for Chaotic Association, Trends in Neural Computation (Studies in Computational Intelligence) (ed. Ke Chen and Lipo Wang), Vol.35, Chapter 5, pp.111-133, Springer-Verlag (New York, USA), 2007 [ISBN: 978-3-540-36121-3].
    Download: Full Chapter (SpringerLink)PDF

  14. Kobayashi, K., Self-organizing Wavelet-based Neural Networks, Time-Frequency and Wavelets in Biomedical Signal Processing (ed. Metin Akay, IEEE Press Series on Biomedical Engineering), Part IV: Wavelets, Neural Networks, and Fractals, Chapter 28, pp.685-702, IEEE Press (Wiley-IEEE Press), 1997 [ISBN: 978-0-7803-1147-3].

Invited talk:

  1. Kobayashi, K., The Influence of Nicotine on Dynamics of AMPA and NMDA Receptors of VTA Neurons, The 1st Advanced Study Institute on Global Healthcare Challenges (ASI2010), July 15-23, 2010 (Akdeniz University, Antalya, Turkey).

Journal papers (translated in English):

  1. Kuremoto, T., Watanabe, S., Kobayashi, K., Feng, L., and Obayashi, M., The Dynamical Recollection of Interconnected Neural Networks Using Meta-heuristics, Electronics and Communications in Japan, Vol.95, No.6, pp.12-23, 2012.
    Download: Full Paper (Willey InterScience)PDF

  2. Obayashi, M., Narita, K., Kobayashi, K., and Kuremoto, T., A Transient Chaotic Associative Memory Model with Temporary Stay Function, Electronics and Communications in Japan, Vol.175, No.2, pp-29-36, 2011.
    Download: Full Paper (Willey InterScience)PDF

  3. Kobayashi, K., Nakano, K., Kuremoto, T., and Obayashi, M., A State Predictor Based Reinforcement Learning System, Electronics and Communications in Japan, Vol.93, No.6, pp.8-18, 2010.
    Download: Full Paper (Willey InterScience)PDF

  4. Obayashi, M., Omiya, R., Kuremoto, T., and Kobayashi, K., Shapes of Nonmonotonic Activation Functions in a Chaotic Neural Network Associative Memory Model and Its Evaluation, Electronics and Communications in Japan, Vol.91, No.3, pp22-27, 2008.
    Download: Full Paper (Willey InterScience)PDF

  5. Umesako, K., Obayashi, M., and Kobayashi, K., Evolutionary Reinforcement Learning System with Time-varying Parameters, Electrical Engineering in Japan, Vol.156, No.1, pp.54-60, 2006.
    Download: Full Paper (Willey InterScience)PDF

  6. Kobayashi, K., Torioka, T., and Yoshida, N., A Wavelet Neural Network with Network Optimizing Function, Systems and Computers in Japan, Vol.26, No.9, pp.61-71, 1995.
    Download: Full Paper (Willey InterScience)PDF

  7. Kobayashi, K., Hara, H., and Torioka, T., Pattern Separation Function of Two-layered Random Net with Feedforward Inhibitory Connections, Systems and Computers in Japan, Vol.26, No.4, pp.42-51, 1995.
    Download: Full Paper (Willey InterScience)PDF

Proceedings of domestic conferences:

You can download the list of the papers presented at domestic conferences. Note that the list is written in Japanese.
Download: Full listPDF


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