Policy gradient stochastic approximation algorithms for adaptive control of constrained time varying markov decision processes

2004 ◽  
Author(s):  
F.J. Vazquez Abad ◽  
V. Krishnamurthy
Keyword(s):  
Adaptive Control ◽  
Approximation Algorithms ◽  
Markov Decision Processes ◽  
Stochastic Approximation ◽  
Decision Processes ◽  
Time Varying ◽  
Policy Gradient ◽  
Markov Decision

scholarly journals Policy gradient in Lipschitz Markov Decision Processes

2015 ◽  
Vol 100 (2-3) ◽  
pp. 255-283 ◽  
Author(s):  
Matteo Pirotta ◽  
Marcello Restelli ◽  
Luca Bascetta
Keyword(s):  
Markov Decision Processes ◽  
Decision Processes ◽  
Policy Gradient ◽  
Markov Decision

Adaptive control of M/M/1 queues—continuous-time Markov decision process approach

1983 ◽  
Vol 20 (02) ◽  
pp. 368-379
Author(s):  
Lam Yeh ◽  
L. C. Thomas
Keyword(s):  
Adaptive Control ◽  
Markov Decision Process ◽  
Markov Decision Processes ◽  
Optimal Policy ◽  
Continuous Time ◽  
Decision Process ◽  
Process Approach ◽  
Decision Processes ◽  
Markov Decision ◽  
Discounted Costs

By considering continuous-time Markov decision processes where decisions can be made at any time, we show in the case of M/M/1 queues with discounted costs that there exists a monotone optimal policy among all the regular policies.

Adaptive control of M/M/1 queues—continuous-time Markov decision process approach

1983 ◽  
Vol 20 (2) ◽  
pp. 368-379 ◽  
Author(s):  
Lam Yeh ◽  
L. C. Thomas
Keyword(s):  
Adaptive Control ◽  
Markov Decision Process ◽  
Markov Decision Processes ◽  
Optimal Policy ◽  
Continuous Time ◽  
Decision Process ◽  
Process Approach ◽  
Decision Processes ◽  
Markov Decision ◽  
Discounted Costs

By considering continuous-time Markov decision processes where decisions can be made at any time, we show in the case of M/M/1 queues with discounted costs that there exists a monotone optimal policy among all the regular policies.

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