Idiotypic Immune Networks in Mobile Robot Control

Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for...

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Main Authors: Whitbrook, Amanda, Aickelin, Uwe, Garibaldi, Jon
Format: Article
Published: 2007
Online Access:https://eprints.nottingham.ac.uk/654/
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author Whitbrook, Amanda
Aickelin, Uwe
Garibaldi, Jon
author_facet Whitbrook, Amanda
Aickelin, Uwe
Garibaldi, Jon
author_sort Whitbrook, Amanda
building Nottingham Research Data Repository
collection Online Access
description Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.
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spelling nottingham-6542020-05-04T20:29:17Z https://eprints.nottingham.ac.uk/654/ Idiotypic Immune Networks in Mobile Robot Control Whitbrook, Amanda Aickelin, Uwe Garibaldi, Jon Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers. 2007 Article PeerReviewed Whitbrook, Amanda, Aickelin, Uwe and Garibaldi, Jon (2007) Idiotypic Immune Networks in Mobile Robot Control. IEEE Transactions on Systems, Man and Cybernetics Part B . (In Press) doi:10.1109/TSMCB.2007.907334 doi:10.1109/TSMCB.2007.907334
spellingShingle Whitbrook, Amanda
Aickelin, Uwe
Garibaldi, Jon
Idiotypic Immune Networks in Mobile Robot Control
title Idiotypic Immune Networks in Mobile Robot Control
title_full Idiotypic Immune Networks in Mobile Robot Control
title_fullStr Idiotypic Immune Networks in Mobile Robot Control
title_full_unstemmed Idiotypic Immune Networks in Mobile Robot Control
title_short Idiotypic Immune Networks in Mobile Robot Control
title_sort idiotypic immune networks in mobile robot control
url https://eprints.nottingham.ac.uk/654/
https://eprints.nottingham.ac.uk/654/