Papers

6

Total Citations

222

H-Index

6

About

Charles Taylor’s research career bridges two fascinating domains: evolutionary computation and computational bioacoustics. In the late 1990s, Taylor made foundational contributions to evolutionary computation, authoring the highly cited overview “Evolutionary Computation: An Overview” (112 citations), which helped define the field’s core principles. His early work on evolving artificial neural networks to control wandering behavior in small Lego robots (45 citations) demonstrated how biological evolution could inspire robotic control systems. More recently, Taylor has pioneered semi-automated bird song analysis, developing spatial-cue-based probabilistic models that integrate sound source detection, localization, separation, and identification. His 2016 paper on this topic (27 citations) and subsequent 2017 work (10 citations) address the challenging real-world problem of analyzing complex acoustic scenes in animal behavior research. Taylor’s work on the learning and emergence of mildly context-sensitive languages (2003, 11 citations) further showcases his computational linguistics interests. With over 200 total citations spanning two decades, Taylor’s career exemplifies how computational methods can illuminate both artificial and natural intelligence—from evolving robot controllers to decoding the songs of birds.

Research Focus

Key Achievements

6
H-Index
6
Papers
222
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Evolutionary Computation: An Overview
112 citations · 1999
📈 Most Prolific Year: 1994 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Santa Fe Institute, University of California, Los Angeles

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago