Dynamic State Aggregation
Dynamic State Aggregation is a computational method in reinforcement learning and decision-making systems that dynamically groups or partitions environmental states into aggregated representations based on evolving temporal or structural dependencies, thereby distinguishing itself from static or pre-defined state aggregation techniques by adapting to non-stationary dynamics in real time.
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Publications
211
Citations
38
Authors
18
Institutions
Publications per year
2017–2026
3
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8
Yu Ouyang, Pu Zhang, Hadar Manis‐Levy et al. · Journal of the American Chemical Society · 2021 · 54 citations
Dynamic aggregation strategy for a virtual power plant to improve flexible regulation ability
Xin Liu, Yang Li, Li Wang et al. · Energy · 2024 · 40 citations
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Hebrew University of Jerusalem
Jerusalem, Israel
1 h-index
5 publications
270 citations
Jilin University
Changchun, China
1 h-index
5 publications
170 citations

Southeast University
Nanjing, China
1 h-index
3 publications
120 citations
State Key Laboratory of Supramolecular Structure and Materials
Changchun, China
1 h-index
5 publications
170 citations
Helmholtz-Institute Ulm
Ulm, Germany
1 h-index
2 publications
34 citations
Universität Ulm
Ulm, Germany
1 h-index
10 publications
170 citations
Nanyang Technological University
Singapore, Singapore
1 h-index
1 publications
40 citations
Henan Polytechnic University
Jiaozuo, China
1 h-index
1 publications
34 citations
1–8 of 18
1 publications · 40 citations
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1 publications · 15 citations
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JACS · 1 publications · 54 citations
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1 publications · 17 citations
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1 publications · 34 citations
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