Stationary Policy Optimization
Stationary Policy Optimization is a methodological framework within Infinite-Horizon Markov Decision Processes that systematically identifies time-invariant policies maximizing long-term expected reward by restricting the search space to stationary decision rules.
96
Publications
5.3K
Citations
164
Authors
93
Institutions
Publications per year
2017–2026
17
96
Risk-Sensitive Markov Decision Processes
Ronald A. Howard, James Matheson · Management Science · 1972 · 513 citations
An anti-jamming stochastic game for cognitive radio networks
B Wang, Yongle Wu, K J R Liu et al. · IEEE Journal on Selected Areas in Communications · 2011 · 320 citations
Linear Programming and Markov Decision Chains
Arie Hordijk, L. C. M. Kallenberg · Management Science · 1979 · 146 citations
1–5 of 96
164
Universidad Autónoma Agraria Antonio Narro, Mexico
5 publications · 106 citations
5
h-index
4
h-index
4
h-index
3
h-index
3
h-index
1–5 of 164
93

The University of Sydney
Sydney, Australia
4 h-index
11 publications
430 citations
Texas A&M University
College Station, United States
4 h-index
13 publications
347 citations
Stanford University
Stanford, United States
4 h-index
4 publications
1.4K citations
Illinois State University
Normal, United States
3 h-index
3 publications
163 citations
Tsinghua University
Beijing, China
3 h-index
3 publications
100 citations
Stony Brook University
Stony Brook, United States
3 h-index
3 publications
223 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
3 h-index
6 publications
247 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
3 h-index
6 publications
240 citations
1–8 of 93
8 publications · 1.1K citations
8
h-index
8 publications · 1K citations
8
h-index
JAP · 7 publications · 308 citations
7
h-index
6 publications · 301 citations
6
h-index
5 publications · 239 citations
5
h-index
1–5