TATEYAMA Takeshi

Last updated: Jul 10, 2019 at 17:23

Name	TATEYAMA Takeshi
Affiliation	Tokyo Metropolitan University
Section	Faculty of EngineeringDepartment of Precision Engineering
Degree	(BLANK)

Research Interests

discrete-continuous hybrid systems(1) , simulation(189) , deep learning(96) , reinforcement learning(48) , Machine Learning(402)

Research Areas

Mechanical engineering / Intelligent mechanics/Mechanical systems /

Education

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1996

Faculty of Engineering, Tokyo City University

1998

Graduate School, Division of Engineering, Tokyo Metropolitan University

Awards & Honors

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Aug 2006

MOVIC2006(The 8th International Conference on Motion and Vibration Control), Invited Paper Award

Winner: KAWATA Seiichi, TATEYAMA Takeshi

Published Papers

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A Scheduling Support System for Large-scale Facilities Using Reinforcement Learning in Consideration of Skill Educations and Working Conditions

T. Tateyama, T. Tateno and S. Kawata

Journal of Advanced Mechanical Design, Systems, and Manufacturing (JAMDSM) Vol.8(No.5) 2014 [Refereed]

A method for human resource evaluation to realize high-quality PSSs

Y. Shimomura, K. Kimita, T. Tateyama, F. Akasaka and Y. Nemoto

CIRP Annals -Manufacturing Technology Vol.62(No.1) 471-474 2013 [Refereed]

Process Simulation Method for Product-Service Systems Design

K. Kimita, T. Tateyama and Y. Shimomura

Procedia CIRP Vol.3 489-494 2012 [Refereed]

Service Process Simulation for Integrated Service Evaluation

K. Watanabe, S. Mikoshiba, T. Tateyama and Y. Shimomura

Journal of Intelligent Manufacturing, Special issue on: Service Computing and Service Oriented Enterprise Systems in Design, Manufacturing and Supply Chain Vol.23(Issue4) 1379-1388 2011 [Refereed]

Dynamic Work Planning by Using Simulation-based Optimization in Consideration of Workers' Skill and Training

T. Tateyama, T. Tateno and K. Shimizu

Journal of Advanced Mechanical Design, Systems, and Manufacturing (Special issue on Advanced Production Scheduling) Vol.4(No.3) 597-604 2010 [Refereed]

Misc

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Extended K-certainty exploration methods for autonomous robotics systems

Proceedings of the 37th SICE Annual Conference Domestic Session Papers Vol. (]G0002[) ((]G0002[)) 629-630 1998

An Efficient Exploration Method Using K-Certainty Exploration Method and Dynamic Programming under Markov Decision Processes

16(1) 20-27 2001

An Improved Reinforcement Learning by Using The Concept Learning for Continuous State and Action.

2001

An Improved Reinforcement Learning by Using The Concept Learning

79-84 2001

Association Memberships

THE JAPAN SOCIETY OF MECHANICAL ENGINEERS(1843) , THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS(685) , THE INSTITUTE OF ELECTRICAL ENGINEERS OF JAPAN(1017)

Research Grants & Projects

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Study on Machine Learning, Reinforcement Learning