Using Genetic Algorithms for Concept Learning
Machine Learning - Special issue on genetic algorithms
The Baldwin effect in the immune system: learning by somatic hypermutation
Adaptive individuals in evolving populations
Inductive genetic programming with immune network dynamics
Advances in genetic programming
Immune network modelling in design optimization
New ideas in optimization
Machine Learning
The Evolution of Emergent Organization in Immune System Gene Libraries
Proceedings of the 6th International Conference on Genetic Algorithms
The Coevolution of Antibodies for Concept Learning
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Robot with a Decentralized Consensus-making Mechanism Based on the Immune System
ISADS '97 Proceedings of the 3rd International Symposium on Autonomous Decentralized Systems
The Immune System as a Prototype of Autonomous Decentralized Systems: An Overview
ISADS '97 Proceedings of the 3rd International Symposium on Autonomous Decentralized Systems
Antibody repertoires and pathogen recognition: the role of germline diversity and somatic hypermutation
An immunological model of distributed detection and its application to computer security
An immunological model of distributed detection and its application to computer security
Architecture for an Artificial Immune System
Evolutionary Computation
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Gene Expression Programming Based on Subexpression Library and Clonal Selection
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Review: The use of computational intelligence in intrusion detection systems: A review
Applied Soft Computing
Engineering Applications of Artificial Intelligence
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This paper describes two extensions to the original DynamiCS: (1) the deletion of memory detectors that are no longer valid and (2) the simulation of gene library evolution. Firstly, DynamiCS is extended in order to decrease the false positive (FP) error rates caused by memory detectors. The extended DynamiCS eliminates memory detectors when they show a poor degree of self-tolerance to new antigens. This system is tested to determine whether surviving memory detectors no longer cause high FP error rates. The results show a marked decrease in FP errors produced by the system but an increase in the amount of costimulation required. The large amount of costimulation can render the system weak for intrusion detection. The second extension to DynamiCS is proposed to resolve this problem. It employs the use of hypermutation to produce the effect of gene library evolution. This is designed to fine-tune generated memory detectors so that the system obtains higher true positive (TP) detection rates without increasing the amount of co-stimulation. The new extension is tested to determine whether it gains high TP detection rates without increasing the amount of costimulation as the result of gene library evolution. The test results prove that hypermutation leads the progress of gene library evolution and thus produces immature detectors that are more tuned to cover existing non-self antigens.