Anthony Horgan
Papers
1
Total Citations
5
H-Index
1
About
Anthony Horgan is a researcher at the forefront of evolutionary robotics and intelligent control systems. His primary focus lies in the intersection of neural network design and autonomous robotic manipulation, with a particular emphasis on developing adaptive controllers for complex mechanical systems. Horgan’s most notable contribution, "Evolving Neural Networks for Robotic Arm Control" (2023), has garnered 5 citations and represents a significant step forward in applying evolutionary algorithms to train neural networks for precise, real-time robotic motion. This work demonstrates how genetic algorithms can optimize network topologies and weights, enabling robotic arms to learn and refine their movements without explicit programming—a breakthrough with implications for manufacturing, prosthetics, and autonomous systems. While his citation count is still growing, Horgan’s research is recognized for its innovative synthesis of evolutionary computation and practical robotics, offering a scalable alternative to traditional reinforcement learning approaches. His work is particularly valuable for students and researchers exploring bio-inspired methods for adaptive control, as it provides a clear framework for evolving efficient neural controllers in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Evolving Neural Networks for Robotic Arm Control5 citations · 2023