Transgenic evolution for classification tasks with hercl
We explore the evolution of programs for classification tasks, using the recently introduced Hierarchical Evolutionary Re-Combination Language (HERCL) which has been designed as an austere and general-purpose language, with a view toward modular evolutionary computation, combining elements from Linear GP with stack-based operations from forth. We show that evolved HERCL programs can successfully learn to perform a variety of benchmark classification tasks, and that performance is enhanced by the sharing of genetic material between tasks.
Blair, A. D. (2015)., Transgenic evolution for classification tasks with hercl, in M. Randall (ed.), Artificial life and computational intelligence, Dordrecht, Springer, pp. 185-195.
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