Papers on “Markov decision process”

Research on “Markov decision process” in the 480 tracked journals: papers per year and category, the journals, institutions and countries publishing it, the keywords studied with it and its most-cited papers. It is not among the most frequent keywords of the last 30 days, so this page has no list of its latest papers. Also as Markdown.

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Key findings#

From 2017 to 2026 (so far), the keyword “Markov decision process” appeared in 741 papers in the tracked journals, most of them in operations research (454), AI (246) and economics (10).
125 of them were published in 2025, against 33 in 2017.
Since 2023, the institutions with the most of these papers were Tsinghua University (14), Southwest Jiaotong University (13) and Eindhoven University of Technology (12).
The journals publishing most of them were Expert Systems with Applications (48), Computers & Industrial Engineering (42) and European Journal of Operational Research (38).
The most-cited of them is “Challenges of real-world reinforcement learning: definitions, benchmarks and analysis” (Machine Learning, 2021), with 662 citations.

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2017	2018	2019	2020	2021	2022	2023	2024	2025	2026 (so far)
Operations Research	27	25	33	41	37	39	53	68	72	59
AI	3	6	6	10	25	37	38	42	48	31
Economics	3	0	0	2	0	1	0	2	0	2
Information Systems	0	0	0	0	1	1	1	2	3	1
Finance	0	1	1	1	1	0	0	1	0	4
Health Economics and Policy	0	0	0	1	0	1	2	0	1	1
Statistics	0	0	0	0	1	1	0	0	1	2
Management	0	0	1	0	0	0	0	1	0	0
All categories	33	32	41	55	65	80	94	116	125	100

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	Expert Systems with Applications	48
2	Computers & Industrial Engineering	42
3	European Journal of Operational Research	38
4	Transportation Research Part E Logistics and Transportation Review	28
5	Transportation Research Part C Emerging Technologies	23
6	Computers & Operations Research	18
7	Annals of Operations Research	17
8	Knowledge-Based Systems	15
9	Applied Intelligence	14
10	Neural Computing and Applications	13

Institutions with the most papers, since 2023
#	Institution	Papers
1	Tsinghua University	14
2	Southwest Jiaotong University	13
3	Eindhoven University of Technology	12
4	Beijing Jiaotong University	10
5	National University of Singapore	10
6	Beihang University	9
7	Huazhong University of Science and Technology	9
8	Hong Kong Polytechnic University	8
9	Shanghai Jiao Tong University	8
10	Shenzhen University	8

Countries with the most papers, since 2023
#	Country	Papers
1	China	233
2	United States	81
3	Netherlands	31
4	United Kingdom	28
5	Hong Kong	25
6	Canada	24
7	Germany	20
8	France	20
9	Singapore	18
10	Italy	15

Keywords with the most papers, since 2023
#	Keyword	Papers
1	deep reinforcement learning	101
2	reinforcement learning	50
3	proximal policy optimization	36
4	approximate dynamic programming	29
5	deep Q-network	21
6	graph neural networks	17
7	reward function design	17
8	Q-learning	16
9	multi-agent reinforcement learning	15

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	662	10.0	Challenges of real-world reinforcement learning: definitions, benchmarks and analysis	Machine Learning	2021-04-22	Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz et al.
2	242	3.2	Deep reinforcement learning based AGVs real-time scheduling with mixed rule for flexible shop floor in industry 4.0	Computers & Industrial Engineering	2020-08-13	Hao Hu, Xiaoliang Jia, Qixuan He et al.
3	203	3.9	How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda	International Journal of Information Management Data Insights	2022-06-28	Vinay Kumar Singh, Shiuann-Shuoh Chen, Minal Singhania et al.
4	192	4.5	Dynamic scheduling for flexible job shop using a deep reinforcement learning approach	Computers & Industrial Engineering	2023-04-21	Yong Gui, Dunbing Tang, Haihua Zhu et al.
5	181	2.2	Dynamic selective maintenance optimization for multi-state systems over a finite horizon: A deep reinforcement learning approach	European Journal of Operational Research	2019-11-07	Yu Liu, Yiming Chen, Tao Jiang

Cite this page

Scholar4AI. (2026). Papers on “Markov decision process”. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/keywords/markov-decision-process

@misc{scholar4ai-keywords-markov-decision-process,
  author = {{Scholar4AI}},
  title = {Papers on “Markov decision process”},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/keywords/markov-decision-process}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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