Improving Artificial-Immune-System-based computing by exploiting intrinsic features of computer architectures

Yiqi Deng, Peter J. Bentley, Alvee Momshad
2016 2016 IEEE Symposium Series on Computational Intelligence (SSCI)  
Biological systems have become highly significant for traditional computer architectures as examples of highly complex self-organizing systems that perform tasks in parallel with no centralized control. However, few researchers have compared the suitability of different computing approaches for the unique features of Artificial Immune Systems (AIS) when trying to introduce novel computing architectures, and few consider the practicality of their solutions for real world machine learning
more » ... . We propose that the efficacy of AIS-based computing for tackling real world datasets can be improved by the exploitation of intrinsic features of computer architectures. This paper reviews and evaluates current existing implementation solutions for AIS on different computing paradigms and introduces the idea of "C Principles" and "A Principles". Three Artificial Immune Systems implemented on different architectures are compared using these principles to examine the possibility of improving AIS through taking advantage of intrinsic hardware features.
doi:10.1109/ssci.2016.7850157 dblp:conf/ssci/DengBM16 fatcat:34jvqp74ojcijdz4np6c7ekzsi