Chebyshev Scalarization
Chebyshev Scalarization is a scalarization method in multi-objective Markov decision processes that transforms a vector-valued objective into a single objective by minimizing the weighted Chebyshev distance between the expected reward vector and a reference point, thereby accommodating non-convex preference structures distinct from linear scalarizations.
5
Publications
339
Citations
15
Authors
10
Institutions
Publications per year
2017–2026
3
5
Jogender Nagar, Douglas H. Werner · IEEE Transactions on Antennas and Propagation · 2017 · 31 citations
Natural Sciences, Computer Science, Electrical Engineering +17
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15
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10
Shandong University
Jinan, China
1 h-index
3 publications
72 citations
Vrije Universiteit Brussel
Brussels, Belgium
1 h-index
3 publications
753 citations
University of Illinois Chicago
Chicago, United States
1 h-index
1 publications
16 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
1 h-index
1 publications
17 citations
Shandong University of Science and Technology
Qingdao, China
1 h-index
1 publications
24 citations
Linyi University
Linyi, China
1 h-index
1 publications
24 citations

The University of Melbourne
Melbourne, Australia
1 h-index
1 publications
17 citations
Clemson University
Clemson, United States
1 h-index
2 publications
32 citations
1–8 of 10
1 publications · 16 citations
1
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1 publications · 31 citations
1
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1 publications · 17 citations
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1 publications · 24 citations
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1 publications · 17 citations
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