Idiotypic Immune Networks in Mobile-Robot Control

Whitbrook, Amanda; Aickelin, U.; Garibaldi, Jon

Abstract

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.

Citation

Whitbrook, A., Aickelin, U., & Garibaldi, J. (2007). Idiotypic Immune Networks in Mobile-Robot Control. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37(6), 1581-1598. https://doi.org/10.1109/tsmcb.2007.907334

• Journal Article Type: Article
• Publication Date: 2007-12
• Deposit Date: Oct 30, 2007
• Publicly Available Date: Dec 31, 2007
• Journal: IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
• Print ISSN: 1083-4419
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 37
• Issue: 6
• Pages: 1581-1598
• DOI: https://doi.org/10.1109/tsmcb.2007.907334
• Keywords: Control and Systems Engineering; Human-Computer Interaction; Electrical and Electronic Engineering; Software; Information Systems; General Medicine; Computer Science Applications
• Public URL: https://nottingham-repository.worktribe.com/output/1018048
• Publisher URL: https://ieeexplore.ieee.org/document/4362696/
• Additional Information: ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.