Amanda Whitbrook
University of Derby, University of Nottingham, Loughborough University
Papers
11
Total Citations
395
H-Index
8
About
Amanda Whitbrook is a researcher whose work spans two compelling and complementary domains: artificial immune systems (AIS) applied to robotics, and distributed task allocation in multi-robot and multi-agent systems. Her early career established her as a leading voice in biologically-inspired robot control, particularly through her investigations of Jerne's idiotypic network theory as a framework for mobile robot navigation and behavior learning. Papers such as "Idiotypic Immune Networks in Mobile-Robot Control" (83 citations) and her subsequent work on short-term learning architectures and two-timescale learning demonstrated how immune-inspired models could provide adaptive, scalable control for autonomous robots across different hardware platforms. Whitbrook's research evolved to tackle the challenging problem of coordinating multiple robots under real-world constraints. Her most-cited work, "Distributed Task Rescheduling With Time Constraints for the Optimization of Total Task Allocations in a Multirobot System" (146 citations), represents a significant advance in maximizing efficient task completion within time-critical distributed systems. Her broader contributions include accessible educational resources, notably a programming guide for mobile robots, and survey-level work on artificial immune systems. With over 390 total citations, Whitbrook's research has meaningfully shaped both bio-inspired computing and practical multi-robot coordination.
Research Focus
Key Achievements
Top Papers
- 1
- 2Idiotypic Immune Networks in Mobile-Robot Control83 citations · 2007
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- 4Artificial Immune Systems39 citations · 2010
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