Active Object Searching Based on Deep Reinforcement Learning

2020 International Conference on Computing and Data Science (CDS) ◽

10.1109/cds49703.2020.00076 ◽

2020 ◽

Author(s):

Renjie Mao

Keyword(s):

Reinforcement Learning ◽

Active Object ◽

Object Searching

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Active Object Searching on Mobile Robot Using Reinforcement Learning

2021 2nd International Conference on Computing and Data Science (CDS) ◽

10.1109/cds52072.2021.00058 ◽

2021 ◽

Author(s):

Nuo Xu

Keyword(s):

Reinforcement Learning ◽

Mobile Robot ◽

Active Object ◽

Object Searching

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Active Object Perceiver: Recognition-Guided Policy Learning for Object Searching on Mobile Robots

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros.2018.8593720 ◽

2018 ◽

Author(s):

Xin Ye ◽

Zhe Lin ◽

Haoxiang Li ◽

Shibin Zheng ◽

Yezhou Yang

Keyword(s):

Mobile Robots ◽

Policy Learning ◽

Active Object ◽

Object Searching

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End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2019.2899570 ◽

2020 ◽

Vol 42 (6) ◽

pp. 1317-1332 ◽

Author(s):

Wenhan Luo ◽

Peng Sun ◽

Fangwei Zhong ◽

Wei Liu ◽

Tong Zhang ◽

...

Keyword(s):

Reinforcement Learning ◽

Object Tracking ◽

Active Object ◽

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Active Object Localization with Deep Reinforcement Learning

2015 IEEE International Conference on Computer Vision (ICCV) ◽

10.1109/iccv.2015.286 ◽

2015 ◽

Author(s):

Juan C. Caicedo ◽

Svetlana Lazebnik

Keyword(s):

Reinforcement Learning ◽

Object Localization ◽

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Handling Camera Movement Constraints in Reinforcement Learning Based Active Object Recognition

Lecture Notes in Computer Science - Pattern Recognition ◽

10.1007/11861898_64 ◽

2006 ◽

pp. 637-646 ◽

Author(s):

Christian Derichs ◽

Heinrich Niemann

Keyword(s):

Reinforcement Learning ◽

Object Recognition ◽

Active Object ◽

Active Object Recognition

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Active object recognition by view integration and reinforcement learning

Robotics and Autonomous Systems ◽

10.1016/s0921-8890(99)00079-2 ◽

2000 ◽

Vol 31 (1-2) ◽

pp. 71-86 ◽

Author(s):

Lucas Paletta ◽

Axel Pinz

Keyword(s):

Reinforcement Learning ◽

Object Recognition ◽

Active Object ◽

View Integration ◽

Active Object Recognition

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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 ◽

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 ◽

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 ◽

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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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