Multi-objective Reward Design
Multi-Objective Reward Design is a reward design framework that integrates multiple, potentially conflicting objectives into a single reward signal by systematically balancing their relative trade-offs and priorities in reinforcement learning or decision-making systems.
15
Publications
546
Citations
66
Authors
26
Institutions
Publications per year
2017–2026
15
Parents
15
Unexpected Collision Avoidance Driving Strategy Using Deep Reinforcement Learning
Myounghoe Kim, Seongwon Lee, Jaehyun Lim et al. · IEEE Access · 2020 · 44 citations · Full text
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China Three Gorges University
Yichang, China
1 h-index
7 publications
189 citations
Yonsei University
Seoul, South Korea
1 h-index
4 publications
176 citations
University of Science and Technology of China
Hefei, China
1 h-index
1 publications
34 citations

Carleton University
Ottawa, Canada
1 h-index
1 publications
182 citations
University of Alabama in Huntsville
Huntsville, United States
1 h-index
2 publications
22 citations
Technical University of Munich
Munich, Germany
1 h-index
2 publications
68 citations
Tsinghua University
Beijing, China
1 h-index
1 publications
34 citations
ETH Zurich
Zurich, Switzerland
1 h-index
3 publications
111 citations
1–8 of 26
4 publications · 263 citations
3
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Repository · 2 publications · 28 citations
2
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1 publications · 57 citations
1
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1 publications · 34 citations
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1 publications · 23 citations
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