Evolutionary Neural Controllers
Evolutionary Neural Controllers is a computational framework within evolutionary robotics that employs evolutionary algorithms to automatically design and optimize neural network-based control systems for autonomous agents, distinguishing itself from traditional control methods by enabling adaptive, task-specific behavioral learning through simulated natural selection.
313
Publications
14.3K
Citations
615
Authors
290
Institutions
Publications per year
2017–2026
49
Parents
313
1–5 of 313
615
18
h-index
Institute of Cognitive Sciences and Technologies, Italy
11 publications · 1.1K citations
10
h-index
9
h-index
Iscte – Instituto Universitário de Lisboa, Portugal
8 publications · 362 citations
8
h-index
8
h-index
1–5 of 615
290
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
15 h-index
41 publications
3.6K citations
University of Sussex
Brighton, United Kingdom
10 h-index
30 publications
1.3K citations

University of Essex
Colchester, United Kingdom
8 h-index
20 publications
1.4K citations

University of Edinburgh
Edinburgh, United Kingdom
7 h-index
13 publications
978 citations
The University of Texas at Austin
Austin, United States
7 h-index
15 publications
480 citations
Université Libre de Bruxelles
Brussels, Belgium
7 h-index
15 publications
417 citations
National Research Council
Rome, Italy
6 h-index
8 publications
944 citations
Institute of Cognitive Sciences and Technologies
Rome, Italy
6 h-index
10 publications
225 citations
1–8 of 290
10 publications · 962 citations
10
h-index
8 publications · 267 citations
8
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8 publications · 840 citations
8
h-index
7 publications · 353 citations
7
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5 publications · 99 citations
5
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1–5