Mark Neal
Papers
21
Total Citations
464
H-Index
13
About
Mark Neal is a pioneer in biologically inspired robotics, exploring how principles from biology—particularly endocrinology, immunology, and emotional systems—can create more adaptive, autonomous machines. His work bridges artificial life and practical engineering, with a focus on developing robots that can learn, regulate their own behavior, and operate for extended periods in remote environments. Neal’s most influential contributions include the Artificial Homeostatic System (54 citations), which introduced a novel approach to robotic self-regulation, and the adaptive neuro-endocrine system (44 citations), enabling robots to learn associations between sensors and actions in real time. He also advanced the provocative idea that “timidity” could be a useful emotional mechanism for robot control (43 citations), challenging conventional views on robotic decision-making. In applied robotics, Neal co-developed autonomous sailing robots for long-term ocean observation (37 citations), addressing critical design challenges for sustained operation at sea (34 citations). His work on artificial endocrine controllers for power management (28 citations) and chemical detection using immune-inspired algorithms (21 citations) further demonstrates the breadth of his impact. With over 350 total citations, Neal’s research continues to inspire new generations of roboticists to look to nature for solutions to autonomy, adaptation, and resilience.
Research Focus
Key Achievements
Top Papers
- 1Artificial Homeostatic System: A Novel Approach54 citations · 2005
- 2An adaptive neuro-endocrine system for robotic systems44 citations · 2009
- 3Timidity: A useful emotional mechanism for robot control?43 citations · 2003
- 4An Autonomous Sailing Robot for Ocean Observation37 citations · 2006
- 5Once More Unto the Breach35 citations · 2005
- 6
- 7Timidity: A Useful Mechanism for Robot Control?30 citations · 2003
- 8Artificial Endocrine Controller for Power Management in Robotic Systems28 citations · 2013
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- 10Chemical Detection Using the Receptor Density Algorithm21 citations · 2012