Stochastic Shortest Path Problems
Stochastic Shortest Path Problems is a type of Markov decision process that involves finding an optimal policy to reach a designated goal state with minimum expected cost in a stochastic environment where transitions and costs are governed by probability distributions.
217
Publications
10K
Citations
457
Authors
246
Institutions
Publications per year
2017–2026
52
Variants
SspStochastic Shortest Path Problem
Parents
217
1–5 of 217
457
Massachusetts Institute of Technology, United States
7 publications · 901 citations
7
h-index
6
h-index
University of Electronic Science and Technology of China, China
6 publications · 298 citations
6
h-index
6
h-index
Hong Kong Polytechnic University, Hong Kong SAR China
5 publications · 398 citations
5
h-index
1–5 of 457
246
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
24 publications
2.1K citations
Nanyang Technological University
Singapore, Singapore
5 h-index
18 publications
834 citations
Decision Systems (United States)
Northbrook, United States
5 h-index
7 publications
1.3K citations

Australian National University
Canberra, Australia
5 h-index
10 publications
249 citations
Aalborg University
Aalborg, Denmark
5 h-index
14 publications
595 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
5 h-index
13 publications
1.2K citations
The University of Texas at Austin
Austin, United States
5 h-index
11 publications
269 citations
Tsinghua University
Beijing, China
4 h-index
6 publications
288 citations
1–8 of 246
9 publications · 694 citations
9
h-index
6 publications · 191 citations
6
h-index
5 publications · 427 citations
5
h-index
5 publications · 573 citations
5
h-index
TRR · 5 publications · 105 citations
5
h-index
1–5