Reinforcement Learning Applied to Cognitive Space Communications

2019 IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW) ◽

10.1109/ccaaw.2019.8904912 ◽

2019 ◽

Author(s):

Carson D. Schubert ◽

Rigoberto Roche ◽

Janette C. Briones

Keyword(s):

Reinforcement Learning ◽

Space Communications ◽

Cognitive Space

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Multi-objective reinforcement learning-based deep neural networks for cognitive space communications

2017 Cognitive Communications for Aerospace Applications Workshop (CCAA) ◽

10.1109/ccaaw.2017.8001880 ◽

2017 ◽

Author(s):

Paulo Victor R. Ferreira ◽

Randy Paffenroth ◽

Alexander M. Wyglinski ◽

Timothy M. Hackett ◽

Sven G. Bilen ◽

...

Keyword(s):

Neural Networks ◽

Reinforcement Learning ◽

Deep Neural Networks ◽

Space Communications ◽

Multi Objective ◽

Cognitive Space

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High precision uplink time and frequency calibration in cognitive space communications

2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) ◽

10.1109/icci-cc.2015.7259372 ◽

2015 ◽

Author(s):

Menglu Wang ◽

Xi Chen ◽

Wenyun Gao

Keyword(s):

High Precision ◽

Space Communications ◽

Cognitive Space ◽

Frequency Calibration

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Cognitive Space and Linguistic Case

10.1017/cbo9780511551321 ◽

1995 ◽

Author(s):

Izchak M. Schlesinger

Keyword(s):

Cognitive Space

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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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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

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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