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Using Genetic Improvement & Code Transplants to Specialise

Genetic Improvement (GI) is a form of Genetic Programming that improves an existing program. We use GI to evolve a faster version of a C++ program, a Boolean satisfiability (SAT) solver called MiniSAT, specialising it for a particular problem class, namely Combinatorial Interaction Testing (CIT), using automated code transplantation. Our GI-evolved solver achieves overall 17% improvement, making it comparable with average expert human performance. Additionally, this automatically evolved solver is faster than any of the human-improved solvers for the CIT problem.
Speaker Name: 
Justyna Petke
Speaker Bio: 
Research associate at University College London
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Seminar Date: 
Friday, 23 January, 2015 (All day)
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