Jared Moore

Papers

2

Total Citations

5

H-Index

2

About

Jared Moore is a researcher in evolutionary robotics and computational intelligence, with a focus on making complex simulations accessible through web-based platforms. His work bridges the gap between traditional evolutionary algorithms and modern web technologies, enabling broader participation in robotics research. Moore's most cited paper, "Evolutionary Robotics on the Web with WebGL and Javascript" (2014), pioneered the use of browser-based 3D physics simulations for evolutionary robotics, overcoming previous limitations in web accessibility and interactivity. This contribution has garnered 3 citations, highlighting its foundational role in democratizing ER experimentation. In "The Limits of Lexicase Selection in an Evolutionary Robotics Task" (2019), Moore critically examined the constraints of lexicase selection, a popular parent selection method, providing insights into its effectiveness in real-world robotics tasks. His work is notable for its practical approach to algorithm evaluation, offering valuable guidance for researchers designing evolutionary systems. Moore's achievements include advancing open-source tools and methodologies that lower barriers to entry in evolutionary robotics, making him a key figure in the integration of web technologies with artificial life research.

Research Focus

Key Achievements

2
H-Index
2
Papers
5
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Evolutionary Robotics on the Web with WebGL and Javascript
3 citations · 2014
📈 Most Prolific Year: 2014 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago