Lateral Intraparietal Cortex and Reinforcement Learning during a Mixed-Strategy Game

Journal of Neuroscience ◽

10.1523/jneurosci.1479-09.2009 ◽

2009 ◽

Vol 29 (22) ◽

pp. 7278-7289 ◽

Author(s):

H. Seo ◽

D. J. Barraclough ◽

D. Lee

Keyword(s):

Reinforcement Learning ◽

Mixed Strategy ◽

Lateral Intraparietal Cortex ◽

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The Stochastic Neural Decision Process and Modelling Choice in a Mixed Strategy Game

SSRN Electronic Journal ◽

10.2139/ssrn.1949732 ◽

2011 ◽

Author(s):

Ryan Webb

Keyword(s):

Decision Process ◽

Mixed Strategy ◽

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Prefrontal cortex and decision making in a mixed-strategy game

Nature Neuroscience ◽

10.1038/nn1209 ◽

2004 ◽

Vol 7 (4) ◽

pp. 404-410 ◽

Author(s):

Dominic J Barraclough ◽

Michelle L Conroy ◽

Daeyeol Lee

Keyword(s):

Decision Making ◽

Prefrontal Cortex ◽

Mixed Strategy ◽

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Combining Case-Based Reasoning and Reinforcement Learning for Unit Navigation in Real-Time Strategy Game AI

Case-Based Reasoning Research and Development - Lecture Notes in Computer Science ◽

10.1007/978-3-319-11209-1_36 ◽

2014 ◽

pp. 511-525 ◽

Author(s):

Stefan Wender ◽

Ian Watson

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Case Based Reasoning ◽

Game Ai ◽

Strategy Game ◽

Real Time Strategy Game ◽

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The Application of Co-evolutionary Genetic Programming and TD(1) Reinforcement Learning in Large-Scale Strategy Game VCMI

Agent and Multi-Agent Systems: Technologies and Applications - Smart Innovation, Systems and Technologies ◽

10.1007/978-3-319-19728-9_7 ◽

2015 ◽

pp. 81-93 ◽

Author(s):

Łukasz Wilisowski ◽

Rafał Dreżewski

Keyword(s):

Reinforcement Learning ◽

Genetic Programming ◽

Large Scale ◽

Evolutionary Genetic ◽

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Behavioral and Neural Variability Related to Stochastic Choices during a Mixed-Strategy Game

The Dynamic Brain ◽

10.1093/acprof:oso/9780195393798.003.0012 ◽

2011 ◽

pp. 255-275 ◽

Author(s):

Daeyeol Lee ◽

Hyojung Seo

Keyword(s):

Mixed Strategy ◽

Strategy Game ◽

Neural Variability

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Playing a Strategy Game with Knowledge-Based Reinforcement Learning

SN Computer Science ◽

10.1007/s42979-020-0087-8 ◽

2020 ◽

Vol 1 (2) ◽

Author(s):

Viktor Voss ◽

Liudmyla Nechepurenko ◽

Rudi Schaefer ◽

Steffen Bauer

Keyword(s):

Reinforcement Learning ◽

Knowledge Based ◽

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A Distributed Control Method for Urban Networks Using Multi-Agent Reinforcement Learning Based on Regional Mixed Strategy Nash-Equilibrium

IEEE Access ◽

10.1109/access.2020.2968937 ◽

2020 ◽

Vol 8 ◽

pp. 19750-19766 ◽

Author(s):

Zhaowei Qu ◽

Zhaotian Pan ◽

Yongheng Chen ◽

Xin Wang ◽

Haitao Li

Keyword(s):

Reinforcement Learning ◽

Nash Equilibrium ◽

Distributed Control ◽

Mixed Strategy ◽

Control Method ◽

Urban Networks ◽

Mixed Strategy Nash Equilibrium ◽

Multi Agent ◽

Strategy Nash Equilibrium

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A Human Mixed Strategy Approach to Deep Reinforcement Learning

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc.2018.00682 ◽

2018 ◽

Author(s):

Ngoc Duy Nguyen ◽

Saeid Nahavandi ◽

Thanh Nguyen

Keyword(s):

Reinforcement Learning ◽

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A system dynamics model for a mixed-strategy game between police and driver

System Dynamics Review ◽

10.1002/(sici)1099-1727(199721)13:1<33::aid-sdr114>3.0.co;2-y ◽

1997 ◽

Vol 13 (1) ◽

pp. 33-52 ◽

Author(s):

Dong-Hwan Kim ◽

Doa Hoon Kim

Keyword(s):

System Dynamics ◽

Mixed Strategy ◽

System Dynamics Model ◽

Dynamics Model ◽

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A mixed strategy game theoretic approach to dynamic load balancing in cellular networks

2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI) ◽

10.1109/icacci.2015.7275590 ◽

2015 ◽

Author(s):

Anshul Mittal ◽

Manish Kumar Sharma

Keyword(s):

Load Balancing ◽

Cellular Networks ◽

Dynamic Load ◽

Mixed Strategy ◽

Dynamic Load Balancing ◽

Theoretic Approach ◽

Game Theoretic ◽

Strategy Game ◽

Game Theoretic Approach

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