Properties of the bersini experiment on self-assertion
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Applicability issues of the real-valued negative selection algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Revisiting Negative Selection Algorithms
Evolutionary Computation
Application areas of AIS: The past, the present and the future
Applied Soft Computing
Artificial Immune Systems and Kernel Methods
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
V-detector: An efficient negative selection algorithm with "probably adequate" detector coverage
Information Sciences: an International Journal
Nonself Detection in a Two-Component Cellular Frustrated System
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Revisiting the central and peripheral immune system
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Topological constraints in the evolution of idiotypic networks
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Structure versus function: a topological perspective on immune networks
Natural Computing: an international journal
Analysis of a growth model for idiotypic networks
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Tolerance vs intolerance: how affinity defines topology in an idiotypic network
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
| Hi-index | 0.00 |
The purpose of this paper is three-fold. Firstly, it aims to demonstrate empirically that networks evolved using different shaped recognition regions in a real-valued shape-space exhibit different dynamics during their formation, and vary in both their capabilities to tolerate antigens and in their memory capacity. Secondly, the paper serves as a useful comparison to previous published work which investigated the properties of a network evolving in a simple, small Hamming shape-space. This work represents the first steps in a proper analysis of a real-valued shape-space with differing recognition shapes. Finally, and perhaps most importantly, the experiments presented illustrate the importance of paying careful attention to the choice of recognition region and algorithm parameters when applying an AIS based on a network-model to practical problems.