kazuhiro ookura

Last Updated :2021/04/06

Affiliations, Positions
Graduate School of Advanced Science and Engineering, Professor
E-mail
kohkurahiroshima-u.ac.jp

Basic Information

Academic Degrees

  • Doctor of Engineering, HOKKAIDO UNIVERSITY
  • Master of Engineering, HOKKAIDO UNIVERSITY

Research Fields

  • Informatics;Human informatics;Intelligent robotics
  • Engineering;Mechanical engineering;Intelligent mechanics / Mechanical systems

Research Keywords

  • Decentralized autonomous systems, Swarm robotics, Machine intelligence

Educational Activity

Course in Charge

  1. 2021, Liberal Arts Education Program1, 2Term, Engineering in the Society
  2. 2021, Liberal Arts Education Program1, 4Term, Introduction to Mechanical Engineering
  3. 2021, Liberal Arts Education Program1, 2Term, Design and Optimization of Mechanical Systems
  4. 2021, Undergraduate Education, 4Term, Data Structure and Algorithm
  5. 2021, Undergraduate Education, 4Term, Systems Engineering
  6. 2021, Undergraduate Education, 3Term, Mechatronics
  7. 2021, Undergraduate Education, Second Semester, Mechanical Engineering Seminar
  8. 2021, Graduate Education (Doctoral Program) , Year, Mechanical Systems Engineering Research V
  9. 2021, Graduate Education (Master's Program) , 1Term, Special Exercises on Mechanical Engineering A
  10. 2021, Graduate Education (Master's Program) , 2Term, Special Exercises on Mechanical Engineering A
  11. 2021, Graduate Education (Master's Program) , 3Term, Special Exercises on Mechanical Engineering B
  12. 2021, Graduate Education (Master's Program) , 4Term, Special Exercises on Mechanical Engineering B
  13. 2021, Graduate Education (Master's Program) , Academic Year, Special Study on Mechanical Engineering
  14. 2021, Graduate Education (Master's Program) , 2Term, Advanced Autonomous Systems Engineering
  15. 2021, Graduate Education (Doctoral Program) , Academic Year, Special Study on Mechanical Engineering

Research Activities

Academic Papers

  1. An Improved Hybrid Artificial Bee Colony Algorithm for Solving Real Parameter Optimization Problems, International Journal of Engineering Research and Technology, 4(5), 628-635, 201505
  2. A Self Adaptive Hybrid Enhanced Artificial Bee Colony Algorithm for Continuous Optimization Problems, BioSystems, 132-133, 43-53, 201506
  3. Robust Swarm Robotics System using CMA-Neuroes with Incremental Evolution, International Journal of Engineering Research and Technology, 4(11), 217-226, 201511
  4. Generating Flocking Behavior of a Real Robotic Swarm that Travels between Two Landmarks, Proceedings of the First International Symposium on Swarm Behavior and Bio-Inspired Robotics, 239-242, 201510
  5. A Parallel Computing Implementation of Evolutionary Swarm Robotics Approach, Proceedings of the First International Symposium on Swarm Behavior and Bio-Inspired Robotics, 235-238, 201510
  6. Understanding Autonomous Task Allocation by Clustering a Swarm Robotics System, Proceedings of the First International Symposium on Swarm Behavior and Bio-Inspired Robotics, 192-193, 201510
  7. A Predator-Prey Artificial World That Yields Swarm Behavior, Proceedings of the First International Symposium on Swarm Behavior and Bio-Inspired Robotics, 190-191, 201510
  8. A duration based behavior analyze approach for swarm robotics system, Proceedings of SICE Annual Conference 2015, 276-281, 201507
  9. An Evolutionary Approach to Sudoku Puzzles with Filtered Mutations, Proceedings of 2015 IEEE Congress on Evolutionary Computation, 1732-1737, 201505
  10. Congestion: A Key Factor for Division of Labor in a Robotic Swarm, Proceedings of the First International Conference on Digital Practice for Science, Technology, Education, and Management, 66-71, 20180307
  11. Collective Behavior Acquisition of Real Robotic Swarms using Deep Reinforcement Learning, Proceedings of the Second IEEE International Conference on Robotic Computing, 179-180, 20180131
  12. Hierarchical Interaction Based Flocking in Swarm Robotic Systems, Proceedings of the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics, 218-220, 20171211
  13. Evolutionary Acquisition of Autonomous Specialization in a Path-Formation Task of a Robotic Swarm, JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS, 22(5), 621-628, 201809
  14. Generating and analyzing hierarchical interaction in a flock of robotic swarms, ARTIFICIAL LIFE AND ROBOTICS, 23(4), 481-488, 201812
  15. Evolving autonomous specialization in congested path formation task of robotic swarms, ARTIFICIAL LIFE AND ROBOTICS, 23(4), 547-554, 201812
  16. A Genetic Algorithm with Neutral Mutations for Deceptive Function Optimization, 32(10), 1461-1469, 19961031
  17. Evolving Behaviors emerged in operon-GA solving Royal Road Functions, 1997(2), 19971001
  18. Real-Valued Engineering Function Optimization by Evolution Strategies that Use Redundant Individual Representation, 35(11), 1469-1477, 19991130
  19. A Cooperatively Coevolutionary Genetic Algorithm to the Dynamic Facility Layout Problems, Transactions of the Institute of Systems, Control and Information Engineers, 15(4), 167-174, 20020415
  20. The Cooperative Behavior Acquisition Problem by a Homogeneous Autonomous Robot Group : An Approach based on Specialization, Transactions of the Institute of Systems, Control and Information Engineers, 15(9), 451-458, 20020915
  21. Characteristic Behavior and Global Behavior in Multi-Agent System, 9, 191-194, 199910
  22. Estimating the Degree of Neutrality in Fitness Landscapes by the Nei's Standard Genetic Distance : An Application to Evolutionary Robotics, Transactions of the Institute of Systems, Control and Information Engineers, 18(8), 284-291, 20050815
  23. Behavior Acquisition of an Autonomous Robot by Reinforcement Learning Based on Globally Coupled Chaotic System : 1st Report, Empirical Examination of Credit Assignment and Generalization, Transactions of the Japan Society of Mechanical Engineers. C, 63(615), 3969-3976, 19971125
  24. Estimation of Fitness Landscapes on Coevolutionary Neural Controller in Cooperative Carrying Problem, FAN Symposium : Intelligent System Symposium-fuzzy, AI, neural network applications technologies, 12, 499-502, 20021114
  25. Reinforcement Learning Control of Autonomous Arm Robots, 2002, 2002
  26. A Consideration on Hardware Evolution of Pulse Neural Network, 2002, 2002
  27. Cooperative Behavior Acquisition of Homogenous Multiple Mobile Robots, 2002, 2002
  28. Topology and Weight Evolving Artificial Neural Network for Autonomous Mobile Robots, 2003, 2003
  29. Biological Manufacturing Systems and Resrarch Topics for Realization, Manufacturing Systems Division Conference, 2003, 53-54, 20030328
  30. Symbiotic revolutionary multi-robot systems : The use of TWEANN, 2004(5), 323-324, 20040904
  31. Cooperative Behavior Acquisition Mechanism for a Autonomous Multi-Robot System by Reinforcement Learning : Increase and Decrease of a Robot, 2004, 189-190, 20040618
  32. 1P1-S-066 Behavior Acquisition of a Multi-Robot System Based on Reinforcement Learning with a Function of Adaptive Segmentation of the Action Space(Evolution and Learning for Robotics 2,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives), 2005, 20050609
  33. 2P1-S-069 A Study on Analysis of Feature of MAS using the Ecological Method(Evolution and Learning for Robotics 5,Mega-Integration in Robotics and Mechatronics to Assist Our Daily Lives), 2005, 20050609
  34. Effectiveness of Kaizen based on Informal Knowledge Management on the Improvement in Group Achievements, Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, 20(6), 972-980, 20081215
  35. 321 Generalization capability of TWEANN in cooperative package pushing problems, Dynamics & Design Conference, 2009, "321-1"-"321-6", 20090803
  36. A Genetic Algorithm for Nonstationary Function Optimization Problems, Transactions of the Institute of Systems, Control and Information Engineers, 8(6), 269-276, 1995
  37. A Genetic Algorithm with Neutral Mutations for Deceptive Function Optimization, Transactions of the Society of Instrument and Control Engineers, 32(10), 1461-1469, 1996
  38. Improving the Robustness of Instance-Based Reinforcement Learning for Multi-Robot Systems, Transactions of the Society of Instrument and Control Engineers, 42(10), 1150-1157, 2006
  39. Generation of Mechanical Assembly Sequences Using CPR Graph. 1st Report. Definition and Usage of CPR Graph., TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series A, 62(595), 1223-1230, 1996
  40. An Evolutionary Autonomous Mobile Robot with An On-line Model Update Mechanism, Proceedings of the Japan Joint Automatic Control Conference, 47(0), 51-51, 2004
  41. Fitness Landscape Description Based on Neutrality, Proceedings of JSPE Semestrial Meeting, 2003(0), 35-35, 2003
  42. Evolutionary Design of Object Classification Systems Using Pulsed Neural Networks, Proceedings of JSPE Semestrial Meeting, 2003(0), 36-36, 2003
  43. Addition of the Element in Evolutionary Artificial Neural Networks, Proceedings of JSPE Semestrial Meeting, 2004(0), 203-203, 2004
  44. Shaping Evolution for Artificial Neural Networks for a Multi-Robot system, Proceedings of JSPE Semestrial Meeting, 2005(0), 671-671, 2005
  45. Cooperative Behavior Acquisition of Autonomous Arm Robots through Reinforcement Learning, Transactions of the Society of Instrument and Control Engineers, 39(3), 266-275, 2003
  46. Adoption of topology and weight evolving artificial neural networks against pole balancing problems, Proceedings of JSPE Semestrial Meeting, 2006(0), 843-844, 2006
  47. Cooperative Behavior Acquisition of Autonomous Arm Robots through Reinforcement Learning, Transactions of the Society of Instrument and Control Engineers, 39(3), 266-275, 20030331
  48. Implementation Method of Genetic Algorithms to the CUDA Environment using Data Parallelization, Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, 23(1), 18-28, 20110215
  49. Swarm : Emergent Collective Behavior Generation in Multi-agent Systems, Journal of The Society of Instrument and Control Engineers, 52(3), 179-182, 20130310
  50. Evolving Artificial Neural Networks for Swarm Robotics, Journal of The Society of Instrument and Control Engineers, 52(3), 240-245, 20130310
  51. Cooperative Behavior Acquisition of Multi-Robot Systems Based on Reinforcement Learning in Continuous Space, 52(7), 648-655, 20130710
  52. Preservation and Utilization of Reinforcement Learning Robot's Strategies Using Probablistic Networks, Transactions of the Japan Society of Mechanical Engineers C, 73(736), 3212-3219, 20071225
  53. Improving Segmentation of Action Space for the Instance-Based Reinforcement Learning Method Called BRL : 1st Report, Behavior Acquisition for a Mobile Robot, Transactions of the Japan Society of Mechanical Engineers C, 74(747), 2747-2754, 20081125
  54. 2P2-G09 Analyzing the Specialization Process of Arm-Type Robots that Perform Reinforcement Learning, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2008(0), _2P2-G09_1-_2P2-G09_4, 2008
  55. 2A2-F24 Application to the learning convergence index of the rule ignition entropy for meta learning in reinforcement learning ability of BRL, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2010(0), _2A2-F24_1-_2A2-F24_4, 2010
  56. 2P1-G09 Incremental Behavior Acquisition using BRL in Multi-Robot Box-Pushing Tasks, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2010(0), _2P1-G09_1-_2P1-G09_4, 2010
  57. Behavior Generation and Analysis of Task Allocation in Evolutionary Swarm Robotic Systems(New Trends of Population-Based Machine Learning), SYSTEMS, CONTROL AND INFORMATION, 57(10), 427-432, 2013
  58. 2B3-2 Parameter Setting for Neural Network as a State Transition Prediction Mechanism for Reinforcement Learning Robots, 2011(21), 311-314, 2011
  59. 2B3-3 Initialization methods of Evolving Artificial Neural Networks : comparison of Shimodaira method with Yamada method, 2011(21), 315-318, 2011
  60. 1A1-M02 Cluster Analysis of Group Behavior in Swarm Robotic Systems : Approach of Complex Networks(Evolution and Learning for Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2011(0), _1A1-M02_1-_1A1-M02_4, 2011
  61. 1A1-M10 Behavior acquisition based on reinforcement learning ability of BRL for autonomous mobile robots with meta-learning mechanism(Evolution and Learning for Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2011(0), _1A1-M10_1-_1A1-M10_4, 2011
  62. 1A1-M12 Implementation Method of Steady-state GA on the CUDA Environment(Evolution and Learning for Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2011(0), _1A1-M12_1-_1A1-M12_4, 2011
  63. 1A1-O04 The analysis of Cooperative Behavior in Reinforcement Learning Multi-Robot Box-Pushing Tasks by using Shaping(Evolution and Learning for Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2011(0), _1A1-O04_1-_1A1-O04_4, 2011
  64. 1A1-O10 Preservation and Application of Acquired Knowledge for Improving a Robustness of Multi-Robot Systems(Evolution and Learning for Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2011(0), _1A1-O10_1-_1A1-O10_4, 2011
  65. 1A1-P03 Acquisition of cooperative behavior with human for autonomous robots by reinforcement learning : Validation of environmental robustness(Evolution and Learning for Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2011(0), _1A1-P03_1-_1A1-P03_4, 2011
  66. 1A1-D10 Cooperative Behavior Acquisition with Reinforcement Learning Robots Based on the Mechanism of Selecting the State Space Representations(Evolution and Learning for Robotics(1)), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2012(0), _1A1-D10_1-_1A1-D10_4, 2012
  67. 1A1-D11 Implementating Island Real-Coded Genetic Algorithms with GPU Computing(Evolution and Learning for Robotics(1)), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2012(0), _1A1-D11_1-_1A1-D11_4, 2012
  68. 1A1-E11 Generation of flocking behavior in autonomous mobile robots based on self-propelled particles model(Evolution and Learning for Robotics(1)), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2012(0), _1A1-E11_1-_1A1-E11_4, 2012
  69. 2P1-I06 Cooperative Behavior Acquisition of a Robotic Swarm Based on Ensemble Reinforcement Learning(Swarm Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2013(0), _2P1-I06_1-_2P1-I06_4, 2013
  70. 2P1-I07 Analysis of Collective Behavior based on Ethology in Foraging Problem(Swarm Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2013(0), _2P1-I07_1-_2P1-I07_4, 2013
  71. FAN-14-002 Self-organized Flocking in a Swarm of Mobile Robots by Topological Distance-Based Interactions, 2014(24), 5-10, 2014
  72. FAN-14-005 Parameter Archive Managing Strategies for SHADE, 2014(24), 23-28, 2014
  73. FAN-14-006 Proposal of Business Support System in the International Services Market : Case Study of a Cleaning Company at Shanghai City in China, 2014(24), 29-32, 2014
  74. FAN-14-024 Understanding Swarm Behavior : A case study of the cooperative foraging problems with a swarm robotics system, 2014(24), 108-112, 2014
  75. 2A2-J03 Experiments for Generating Flocking Behavior of a Real Robotic Swarm(Swarm Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2014(0), _2A2-J03_1-_2A2-J03_4, 2014
  76. 2A2-J06 Collective Behavior Acquisition of a Robotic Swarm Based on Incremental Evolution in a Cooperative Food Foraging Task(Swarm Robotics), The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2014(0), _2A2-J06_1-_2A2-J06_4, 2014
  77. 2A1-K08 Effects of Input-Output Configurations for Flocking Behavior of a Real Robotic Swarm, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2015(0), _2A1-K08_1-_2A1-K08_4, 2015
  78. 2A1-K09 Generating Flocking Behavior of a Real Robotic Swarm that Travels between Two Landmarks, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2015(0), _2A1-K09_1-_2A1-K09_4, 2015
  79. Analysis on Structures of Fitness Landscapes with Both Neutrality and Ruggedness Based on Neutral Networks, Transactions of the Japanese Society for Artificial Intelligence, 25(2), 332-339, 2010
  80. An Extension of Particle Swarm Optimization Based on Partial Initialization (The 1st Report, Performance Evaluation on Test Functions), TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 77(777), 2071-2083, 2011
  81. An Extension of Particle Swarm Optimization Based on Partial Initialization (The 2nd Report, Performance Evaluation on a Multi-Robot System Problem), TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 77(777), 2084-2095, 2011
  82. Coordinating Adaptive Behavior for Swarm Robotics Based on Topology and Weight Evolving Artificial Neural Networks, TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 77(775), 966-979, 2011
  83. Application of R3Q for Medium-Grained Task with Nonuniform Computational Granularity, TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 78(790), 2241-2251, 2012
  84. Network Parameter Setting for Reinforcement Learning Approaches Using Neural Networks, TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 78(792), 2950-2961, 2012
  85. A Method of Analyzing Collective Behavior in a Swarm Robotic System Based on Clustering, TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 78(794), 3529-3540, 2012
  86. Improving Segmentation of Action Space for the Instance-Based Reinforcement Learning Method Called BRL (1st Report, Behavior Acquisition for a Mobile Robot):1st Report, Behavior Acquisition for a Mobile Robot, TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 74(747), 2747-2754, 2008
  87. Implementating Island Genetic Algorithms with GPU, Proceedings of the Fuzzy System Symposium, 27(0), 108-108, 2011
  88. A method of behavior analysis of a swarm robotic system based on complex networks, Proceedings of the Fuzzy System Symposium, 27(0), 306-306, 2011
  89. Feature Quantity of Apparel Industry on Network Analysis, Proceedings of JSPE Semestrial Meeting, 2013(0), 763-764, 2013
  90. GPU Implementation of Food-Foraging Problem for Evolutionary Swarm Robotics Systems, IEEJ Transactions on Electronics, Information and Systems, 134(9), 1355-1364, 2014
  91. Collective Behavior Analysis in Swarm Robotics Systems Based on the Ethological Approach, Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, 26(5), 855-865, 2014
  92. Analyzing the evolutionary process of an incremental evolving robotic swarm based on the ethological approach, Proceedings of JSPE Semestrial Meeting, 2013(0), 287-288, 2013
  93. Hidden Layer Structure of EANN in Swarm Robotic Systems, Proceedings of the Fuzzy System Symposium, 26(0), 265-265, 2010
  94. Introducing a Stochastic Parameter Control Method to an Adaptive Differential Evolution, IEEJ Transactions on Electronics, Information and Systems, 135(9), 1142-1148, 2015
  95. SICE Symposium on Systems and Information 2015, Journal of The Society of Instrument and Control Engineers, 55(5), 458-458, 2016
  96. Network Analyses in the Textile-related Trade:―Network Analyses from the Industrial Side of the Dyeing and Finishing―, JOURNAL of the JAPAN RESEARCH ASSOCIATION for TEXTILE END-USES, 52(12), 777-780, 2011
  97. Collective behavior analysis in swarm robotic systems based on the ethological approach, Proceedings of the Fuzzy System Symposium, 28(0), 1117-1122, 2012
  98. Evolutionary swarm robotics approach to the pursuit problem, Proceedings of JSPE Semestrial Meeting, 2014(0), 1067-1068, 2014
  99. Collective behavior generation of evolutionary robotic swarm in the pursuit problem, Proceedings of the Fuzzy System Symposium, 29(0), 167-167, 2013
  100. Community Extraction of Complex Networks in the Textile-related Trade, JOURNAL of the JAPAN RESEARCH ASSOCIATION for TEXTILE END-USES, 54(1), 76-82, 2013
  101. Complex Network Analyses on BtoB networks on Japanese Textile and Apparel Industry, JOURNAL of the JAPAN RESEARCH ASSOCIATION for TEXTILE END-USES, 58(7), 590-598, 2017
  102. Reconstructing Agent Based Model Considering Pluralistic Internal Fluctuation, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2017(0), 2A1-H10, 2017
  103. Hierarchical Interaction Based Flocking in Swarm Robotic Systems, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2017(0), 2A1-H07, 2017
  104. Collective Behavior Acquisition of Real Robotic Swarms using Deep Reinforcement Learning, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2017(0), 2A1-H08, 2017
  105. Reinforcement learning based on a mechanism of selecting state space representations in multi-robot systems, Transactions of the JSME (in Japanese), 2018
  106. An Introduction to Massively Parallel Computing with GPUs-VI:-An Application of GPU Computing to Evolutionary Swarm Robotic Systems, SYSTEMS, CONTROL AND INFORMATION, 60(12), 542-547, 2016
  107. Developing Physical Simulation Environment based on Distributed Computation for Evolutionary Robotics, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 8(0), 211-211, 2008
  108. Validation of Incremental Learning Ability against Change of the Number of Agents for Multi-Agent Reinforcement Learning, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 8(0), 175-175, 2008
  109. The Evaluation of Generation Alternation Models of Evolutionary Computation on Evolutionary Robotics, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 9(0), 63-63, 2009
  110. Cluster Analysis of Group Behavior in Swarm Robotic Systems, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 10(0), 94-94, 2010
  111. Hidden Layer Structure of EANN in Swarm Robotic Systems, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 10(0), 95-95, 2010
  112. Evolutionary Swarm Robotics based on Physical Simulation, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 9(0), 521-521, 2009
  113. Consideration Regarding Reduction of the Reality Gap in Evolutionary Robotic Swarm, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2016(0), 1A1-05a3, 2016
  114. Reinforcement learning based on a mechanism of selecting state space representations in multi-robot systems, Transactions of the JSME (in Japanese), 84(862), 17-00288-17-00288, 2018
  115. Generating Collective Behavior of a Robotic Swarm in a Two-landmark Navigation Task with Deep Neuroevolution, Proceedings of the Annual Conference of JSAI, 2019(0), 3D3OS4a04-3D3OS4a04, 2019
  116. Improving the Robustness of Instance-Based Reinforcement Learning for Multi-Robot Systems, 42(10), 1150-1157, 20061030
  117. Improving the Search Efficiency in the Action Space of a Reinforcement Learning Technique for Multi-Robot Systems, 19, 279-284, 20070129
  118. A Grid Scheduling for an Evolutionary Computation Using R3Q, 47(12), 240-249, 20060915
  119. 4206 Analysis of System Dynamics of MAS using the Ecological Method, The Proceedings of Manufacturing Systems Division Conference, 2006(0), 53-54, 2006
  120. A Study of Developing Collective Behaviour in a Multi-Robot System using Evolving Artificial Neural Networks, 16, 113-116, 20060925
  121. 2A1-M06 Verification Experiments for Improving the Incremental Learning Ability of BRL with Arm-Type Multi-Robot Systems, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2007(0), _2A1-M06_1-_2A1-M06_4, 2007
  122. 2P2-G07 Behavior acquisition of an autonomous mobile robot that passes through a narrow route, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2008(0), _2P2-G07_1-_2P2-G07_4, 2008
  123. 2A2-D10 Acquirement of Surrounding Behavior for Connected Autonomous Mobile Robots based on Reinforcement Learning, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2009(0), _2A2-D10_1-_2A2-D10_4, 2009
  124. 2A2-D14 Convergence behavior acquisition based on reinforcement learning ability of BRL for autonomous mobile robots, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2009(0), _2A2-D14_1-_2A2-D14_4, 2009
  125. 2A2-D16 Experiments on Cooperative Behavior of Arm-Type Robot with a Human Partner : an Approach by Reinforcement Learning, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2009(0), _2A2-D16_1-_2A2-D16_4, 2009
  126. 2P1-G08 The analysis of the function differentiation process in a Reinforcement Learning Two Arm-Type Robots Cooperating with a Human Partner, The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec), 2010(0), _2P1-G08_1-_2P1-G08_4, 2010
  127. An Ecological Approach to the Analysis of Evolutionary Multi-Agent Systems, Proceedings of the Japan Joint Automatic Control Conference, 49(0), 109-109, 2006
  128. The analysis of robot behavior and feature of evolutionary artificial neural networks in multi robot systems, Proceedings of JSPE Semestrial Meeting, 2007(0), 459-460, 2007
  129. Evolutionary robotics approach to cooperative package pushing problems:Searching the hidden layer structure for evolving artificial neural networks, Proceedings of JSPE Semestrial Meeting, 2008(0), 991-992, 2008
  130. Cooperative behavior acquisition of connected autonomous mobile robots by BRL with meta learning., Proceedings of the Fuzzy System Symposium, 26(0), 264-264, 2010
  131. Application and Analysis of Evolving Artificial Neural Networks in Multi Robotics System, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 8(0), 100-100, 2008
  132. A Method of Improving the Robustness of PSO by Introducing the Local Initialization, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 7(0), 181-181, 2007
  133. Grid Scheduling for Evolutionary Multi-Robot Problem, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 7(0), 176-176, 2007
  134. An Analysis of Evolving Artificial Neural Networks using Network Theory, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 8(0), 213-213, 2008
  135. Applying TWEANN to Swarm Robotics, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 9(0), 665-665, 2009
  136. Adoption and Evaluation of GPGPU Approach for Accelerating Genetic Algorithms, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 10(0), 4-4, 2010
  137. Preservation and Utilization of Acquired Knowledge Using Instance - Based Reinforcement Learning, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 10(0), 53-53, 2010
  138. A Study of Generation Alternation Model using Distance among Individuals in Genotype Space, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 10(0), 3-3, 2010
  139. Autonomous adaptation of the hidden layer structure for TWEANN:Artificial evolution of autonomous robot controller, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 9(0), 449-449, 2009
  140. Accelerating genetic algorithms by using a CUDA computing environment, Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers, 9(0), 575-575, 2009
  141. Reinforcement learning based on a mechanism of selecting state space representations in multi-robot systems, Transactions of the JSME, 84(862), 201805
  142. Evolutionary Acquisition of Autonomous Specialization in a Path-Formation Task of a Robotic Swarm, Journal of Advanced Computational Intelligence and Intelligent Informatics, 22(5), 618-628, 2018
  143. Effects of Body Size on Autonomous Specialization and Congestion of Robotic Swarms, Proceedings of the 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems, 85-92, 2018
  144. Towards a Robotic Swarm using Deep Neuroevolution: An Experimental Study in Path Formation, Proceedings of the 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems, 77-80, 2018
  145. Agent-Based Modeling and Complex Network Analysis for Clarifying Changes in the Japanese Textile and Apparel Industry B2B Networks, Proceedings of the 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems, 63-70, 2018
  146. Generating Flocking Behavior in Flying Swarm with Deep Reinforcement Learning, The 50th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 41-42, 2018
  147. Generating Collective Foraging Behavior for Robotic Swarm by Deep Reinforcement Learning, The 50th ISCIE International Symposium on Stochastic Systems Theory and Its Applications, 35-36, 2018
  148. Evolutionary Emergence of Path Formation with Autonomous Specialization in a Robotic Swarm, Proceedings of the 2018 Conference on Artificial Life, 526-527, 2018

Invited Lecture, Oral Presentation, Poster Presentation

  1. Evaluating Optimizers of Deep Reinforcement Learning on Swarm Robotic Systems, Xiaotong Nie, Yufei Wei, Kazuhiro Ohkura, 2018/12/01, Without Invitation, English, preprint
  2. Developing a Robotic Swarm in Unity Based on Robot Operating System (ROS), Wenqian Yu, Ruipeng Ji, Kazuhiro Ohkura, 2018/12/01, Without Invitation, English, preprint
  3. Generating Flocking Behavior in Flying Swarm with Deep Reinforcement Learning, Stefano Kristoforus Sebastian, Jin Boyin, Kazuhiro Ohkura, 2018/05/16, Without Invitation, English, preprint

Awards

  1. 2018/05/17, Best Presentation Award of International Sessions, システム制御情報学会, Generating Flocking Behavior in Flying Swarm with Deep Reinforcement Learning