Competitive Robot Learning
Competitive Robot Learning is a subfield of Multi-Agent Robot Learning in which robotic agents autonomously acquire policies through learning algorithms that explicitly optimize individual performance under adversarial or rivalrous interactions, distinguishing it from cooperative or neutral multi-agent learning paradigms.
22
Publications
973
Citations
70
Authors
30
Institutions
Publications per year
2017–2026
8
Parents
22
1–5 of 22
70
3
h-index
2
h-index
2
h-index
Chongqing Institute of Green and Intelligent Technology, China
2 publications · 76 citations
2
h-index
2
h-index
1–5 of 70
30
Chongqing Institute of Green and Intelligent Technology
Chongqing, China
2 h-index
5 publications
172 citations
Freie Universität Berlin
Berlin, Germany
1 h-index
2 publications
58 citations
University of California San Diego
San Diego, United States
1 h-index
1 publications
91 citations
Jilin University
Changchun, China
1 h-index
2 publications
96 citations
Shenyang Aerospace University
Shenyang, China
1 h-index
1 publications
48 citations
FernUniversität in Hagen
Hagen, Germany
1 h-index
2 publications
58 citations

National Institute of Advanced Industrial Science and Technology
Tsukuba, Japan
1 h-index
2 publications
48 citations

Obuda University
Budapest, Hungary
1 h-index
1 publications
18 citations
1–8 of 30
Repository · 3 publications · 308 citations
3
h-index
AICOM · 1 publications · 20 citations
1
h-index
1 publications · 56 citations
1
h-index
TPAMI · 1 publications · 55 citations
1
h-index
1 publications · 33 citations
1
h-index
1–5