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Updated: Jun 4, 2026

Antigenic Liposomes for Generation of Disease-specific Antibodies
Published on: October 25, 2018
From network-to-antibody robustness in a bio-inspired immune system
Jose A Fernandez-Leon1, Gerardo G Acosta, Miguel A Mayosky
1Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, East Sussex, UK. jf76@sussex.ac.uk
Abstract:
Behavioural robustness at antibody and immune network level is discussed. The robustness of the immune response that drives an autonomous mobile robot is examined with two computational experiments in the autonomous mobile robots trajectory generation context in unknown environments. The immune response is met based on the immune network metaphor for different low-level behaviours coordination. These behaviours are activated when a robot sense the appropriate conditions in the environment in relation to the network current state. Results are obtained over a case study in computer simulation as well as in laboratory experiments with a Khepera II microrobot. In this work, we develop a set of tests where such an immune response is externally perturbed at network or low-level behavioural modules to analyse the robust capacity of the system to unexpected perturbations. Emergence of robust behaviour and high-level immune response relates to the coupling between behavioural modules that are selectively engaged with the environment based on immune response. Experimental evidence leads discussions on a dynamical systems perspective of behavioural robustness in artificial immune systems that goes beyond the isolated immune network response.
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