scholarly journals Applying continuous action reinforcement learning automata(CARLA) to global training of hidden Markov models

2004 ◽  
Author(s):  
J. Kabudian ◽  
M.R. Meybodi ◽  
M.M. Homayounpour
Keyword(s):  
Reinforcement Learning ◽  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Learning Automata ◽  
Continuous Action ◽  
Global Training ◽  
Reinforcement Learning Automata

scholarly journals Multivariable System Identification Method Based on Continuous Action Reinforcement Learning Automata

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 546 ◽  
Author(s):  
Meiying Jiang ◽  
Qibing Jin
Keyword(s):  
Reinforcement Learning ◽  
Mimo Systems ◽  
Attenuation Factor ◽  
Learning Automata ◽  
Learning Ability ◽  
Current Frequency ◽  
Continuous Action ◽  
Domain Identification ◽  
Identification Method ◽  
Reinforcement Learning Automata

In this work, a closed-loop identification method based on a reinforcement learning algorithm is proposed for multiple-input multiple-output (MIMO) systems. This method could be an attractive alternative solution to the problem that the current frequency-domain identification algorithms are usually dependent on the attenuation factor. With this method, after continuously interacting with the environment, the optimal attenuation factor can be identified by the continuous action reinforcement learning automata (CARLA), and then the corresponding parameters could be estimated in the end. Moreover, the proposed method could be applied to time-varying systems online due to its online learning ability. The simulation results suggest that the presented approach can meet the requirement of identification accuracy in both square and non-square systems.

Estimating Personality Impression from Speech Record Using Hidden Markov Models

2015 ◽  
Vol 135 (12) ◽  
pp. 1517-1523 ◽  
Author(s):  
Yicheng Jin ◽  
Takuto Sakuma ◽  
Shohei Kato ◽  
Tsutomu Kunitachi
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov
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