Deterministic policy gradient algorithms for semi‐Markov decision processes

International Journal of Intelligent Systems ◽

10.1002/int.22709 ◽

2021 ◽

Author(s):

Ashkan Haji Hosseinloo ◽

Munther A. Dahleh

Keyword(s):

Markov Decision Processes ◽

Decision Processes ◽

Gradient Algorithms ◽

Policy Gradient ◽

Markov Decision

Download Full-text

Policy gradient in Lipschitz Markov Decision Processes

Machine Learning ◽

10.1007/s10994-015-5484-1 ◽

2015 ◽

Vol 100 (2-3) ◽

pp. 255-283 ◽

Cited By ~ 5

Author(s):

Matteo Pirotta ◽

Marcello Restelli ◽

Luca Bascetta

Keyword(s):

Markov Decision Processes ◽

Decision Processes ◽

Policy Gradient ◽

Markov Decision

Download Full-text

A policy gradient method for semi-Markov decision processes with application to call admission control

European Journal of Operational Research ◽

10.1016/j.ejor.2006.02.023 ◽

2007 ◽

Vol 178 (3) ◽

pp. 808-818 ◽

Cited By ~ 31

Author(s):

Sumeetpal S. Singh ◽

Vladislav B. Tadić ◽

Arnaud Doucet

Keyword(s):

Admission Control ◽

Markov Decision Processes ◽

Gradient Method ◽

Call Admission Control ◽

Decision Processes ◽

Call Admission ◽

Policy Gradient ◽

Markov Decision

Download Full-text

The policy gradient estimation of continuous-time hidden markov decision processes

2005 IEEE International Conference on Information Acquisition ◽

10.1109/icia.2005.1635101 ◽

2006 ◽

Author(s):

Li Yanjie ◽

Yin Baoqun ◽

Xi Hongsheng

Keyword(s):

Markov Decision Processes ◽

Continuous Time ◽

Hidden Markov ◽

Decision Processes ◽

Gradient Estimation ◽

Policy Gradient ◽

Markov Decision

Download Full-text

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

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475) ◽

10.1109/cdc.2003.1273053 ◽

2004 ◽

Cited By ~ 10

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

Download Full-text

An Online Policy Gradient Algorithm for Markov Decision Processes with Continuous States and Actions

Machine Learning and Knowledge Discovery in Databases - Lecture Notes in Computer Science ◽

10.1007/978-3-662-44851-9_23 ◽

2014 ◽

pp. 354-369 ◽

Cited By ~ 1

Author(s):

Yao Ma ◽

Tingting Zhao ◽

Kohei Hatano ◽

Masashi Sugiyama

Keyword(s):

Markov Decision Processes ◽

Decision Processes ◽

Gradient Algorithm ◽

Continuous States ◽

Policy Gradient ◽

Markov Decision

Download Full-text

Learning Control of Dynamical Systems Based on Markov Decision Processes: Research Frontiers and Outlooks

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2012.00673 ◽

2012 ◽

Vol 38 (5) ◽

pp. 673-687 ◽

Cited By ~ 1

Author(s):

Xin XU ◽

Dong SHEN ◽

Yan-Qing GAO ◽

Kai WANG

Keyword(s):

Dynamical Systems ◽

Markov Decision Processes ◽

Learning Control ◽

Decision Processes ◽

Markov Decision ◽

Research Frontiers

Download Full-text

A Framework for Modeling Bounded Rationality: Mis-Specified Bayesian-Markov Decision Processes

SSRN Electronic Journal ◽

10.2139/ssrn.2710475 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ignacio Esponda ◽

Demian Pouzo

Keyword(s):

Bounded Rationality ◽

Markov Decision Processes ◽

Decision Processes ◽

Markov Decision

Download Full-text

A Vector Minimum Superharmonic Approach to Solving Infinite-Horizon Discounted Markov Decision Processes

Journal of the Operational Research Society ◽

10.1038/sj/jors/0431109 ◽

1992 ◽

Vol 43 (11) ◽

pp. 1095-1102

Author(s):

D J White

Keyword(s):

Markov Decision Processes ◽

Infinite Horizon ◽

Decision Processes ◽

Markov Decision

Download Full-text

A Convex Programming Approach for Discrete-Time Markov Decision Processes under the Expected Total Reward Criterion

SIAM Journal on Control and Optimization ◽

10.1137/19m1255811 ◽

2020 ◽

Vol 58 (4) ◽

pp. 2535-2566

Author(s):

François Dufour ◽

Alexandre Genadot

Keyword(s):

Convex Programming ◽

Markov Decision Processes ◽

Discrete Time ◽

Decision Processes ◽

Programming Approach ◽

Total Reward ◽

Markov Decision ◽

Reward Criterion

Download Full-text

Extreme-point solutions in Markov decision processes

Journal of Applied Probability ◽

10.1017/s002190020002413x ◽

1983 ◽

Vol 20 (04) ◽

pp. 835-842

Author(s):

David Assaf

Keyword(s):

Convex Function ◽

Extreme Point ◽

Markov Decision Processes ◽

Convex Functions ◽

Sufficient Conditions ◽

Decision Processes ◽

Markov Decision ◽

Full Solution

The paper presents sufficient conditions for certain functions to be convex. Functions of this type often appear in Markov decision processes, where their maximum is the solution of the problem. Since a convex function takes its maximum at an extreme point, the conditions may greatly simplify a problem. In some cases a full solution may be obtained after the reduction is made. Some illustrative examples are discussed.

Download Full-text