Crossover in Genetic Programming is mostly a destructive operator, generally producing children worse than the parents and occasionally producing those who are better. A recently ...
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
The artificial immune system approach for self-nonself discrimination and its application to anomaly detection problems in engineering is showing great promise. A seminal contribu...
We propose that the behaviour of non-linear media can be controlled automatically through coevolutionary systems. By extension, forms of unconventional computing, i.e., massively ...
Christopher Stone, Rita Toth, Andrew Adamatzky, Be...