Reward Decomposition
Reward Decomposition is a methodological framework in reward design that decomposes a composite reward signal into interpretable and actionable sub-rewards to facilitate learning, credit assignment, and alignment in complex decision-making environments.
11
Publications
922
Citations
36
Authors
19
Institutions
Publications per year
2017–2026
8
Parents
11
Automatic shaping and decomposition of reward functions
Bhaskara Marthi · 2007 · 108 citations · Full text
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Oregon State University
Corvallis, United States
2 h-index
19 publications
757 citations
Tsinghua University
Beijing, China
2 h-index
3 publications
144 citations
Zayed University
Abu Dhabi, United Arab Emirates
1 h-index
1 publications
32 citations
Duke University
Durham, United States
1 h-index
1 publications
267 citations
Örebro University
Örebro, Sweden
1 h-index
3 publications
36 citations
Shandong Institute of Automation
Jinan, China
1 h-index
4 publications
136 citations
William & Mary
Williamsburg, United States
1 h-index
1 publications
267 citations
Williams (United States)
Tulsa, United States
1 h-index
1 publications
267 citations
1–8 of 19
Conference · 1 publications · 129 citations
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1 publications · 205 citations
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1 publications · 32 citations
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TIIS · 1 publications · 64 citations
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1 publications · 34 citations
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