Intelligent Construction Machine by Deep Reinforcement Learning

Masayuki NAKATANI; Zeyuan SUN; Yutaka UCHIMURA

doi:10.1299/jsmermd.2017.2p2-g03

Intelligent Construction Machine by Deep Reinforcement Learning

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2017.2p2-g03 ◽

2017 ◽

Vol 2017 (0) ◽

pp. 2P2-G03

Author(s):

Masayuki NAKATANI ◽

Zeyuan SUN ◽

Yutaka UCHIMURA

Keyword(s):

Reinforcement Learning ◽

Construction Machine

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Route Optimization of Construction Machine by Deep Reinforcement Learning

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.139.401 ◽

2019 ◽

Vol 139 (4) ◽

pp. 401-408

Author(s):

Shunya Tanabe ◽

Zeyuan Sun ◽

Masayuki Nakatani ◽

Yutaka Uchimura

Keyword(s):

Reinforcement Learning ◽

Route Optimization ◽

Construction Machine

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Simulation-based Reinforcement Learning Approach towards Construction Machine Automation

Proceedings of the 37th International Symposium on Automation and Robotics in Construction (ISARC) ◽

10.22260/isarc2020/0064 ◽

2020 ◽

Author(s):

Keita Matsumoto ◽

Atsushi Yamaguchi ◽

Takahiro Oka ◽

Masahiro Yasumoto ◽

Satoru Hara ◽

...

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Construction Machine ◽

Simulation Based

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Optimal routing control of a construction machine by deep reinforcement learning

2018 IEEE 15th International Workshop on Advanced Motion Control (AMC) ◽

10.1109/amc.2019.8371085 ◽

2018 ◽

Author(s):

Zeyuan Sun ◽

Masayuki Nakatani ◽

Yutaka Uchimura

Keyword(s):

Reinforcement Learning ◽

Optimal Routing ◽

Construction Machine ◽

Routing Control

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Supplemental Material for Reconciling Reinforcement Learning Models With Behavioral Extinction and Renewal: Implications for Addiction, Relapse, and Problem Gambling

Psychological Review ◽

10.1037/0033-295x.114.3.784.supp ◽

2007 ◽

Cited By ~ 1

Keyword(s):

Reinforcement Learning ◽

Problem Gambling ◽

Learning Models ◽

Behavioral Extinction ◽

Reinforcement Learning Models

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Bayes factors for reinforcement-learning models of the Iowa gambling task.

Decision ◽

10.1037/dec0000040 ◽

2016 ◽

Vol 3 (2) ◽

pp. 115-131 ◽

Cited By ~ 14

Author(s):

Helen Steingroever ◽

Ruud Wetzels ◽

Eric-Jan Wagenmakers

Keyword(s):

Reinforcement Learning ◽

Iowa Gambling Task ◽

Bayes Factors ◽

Gambling Task ◽

Learning Models ◽

Reinforcement Learning Models

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Analogical Reinforcement Learning With Two-Stage Memory Retrieval

PsycEXTRA Dataset ◽

10.1037/e528942014-705 ◽

2014 ◽

Author(s):

James Foster ◽

Matt Jones

Keyword(s):

Reinforcement Learning ◽

Memory Retrieval ◽

Two Stage

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Effects of Working Memory Capacity on the Speed and Accuracy of Learning in Reinforcement Learning Models

PsycEXTRA Dataset ◽

10.1037/e528942014-552 ◽

2014 ◽

Author(s):

Adnane Ez-Zizi ◽

Simon Farrell ◽

David Leslie

Keyword(s):

Working Memory ◽

Reinforcement Learning ◽

Working Memory Capacity ◽

Memory Capacity ◽

Learning Models ◽

Reinforcement Learning Models ◽

Speed And Accuracy

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Supplemental Material for Reinforcement Learning Models of Risky Choice and the Promotion of Risk-Taking by Losses Disguised as Wins in Rats

Journal of Experimental Psychology Animal Learning and Cognition ◽

10.1037/xan0000141.supp ◽

2017 ◽

Keyword(s):

Reinforcement Learning ◽

Risk Taking ◽

Risky Choice ◽

Learning Models ◽

Losses Disguised As Wins ◽

Reinforcement Learning Models

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Reinforcement learning of irrelevant stimulus-response associations modulates cognitive control.

Journal of Experimental Psychology Learning Memory and Cognition ◽

10.1037/xlm0000850 ◽

2020 ◽

Author(s):

Jinglu Chen ◽

Ling Tan ◽

Lu Liu ◽

Ling Wang

Keyword(s):

Reinforcement Learning ◽

Cognitive Control ◽

Irrelevant Stimulus ◽

Stimulus Response

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A Collaborative Scheduling Lane Changing Model for Intelligent Connected Vehicles Based on Deep Reinforcement Learning

CICTP 2020 ◽

10.1061/9780784483053.178 ◽

2020 ◽

Author(s):

Zheyu Cui ◽

Jianming Hu

Keyword(s):

Reinforcement Learning ◽

Connected Vehicles ◽

Lane Changing ◽

Collaborative Scheduling

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