Genetic Programming with an incremental evolution of complexity

Published in Projects
Project details
ID 5149.13-P
Duration 2012-2014
Funding Dirección General de Educación Superior Tecnológica – México
Objective Develop a new automatic program induction strategy based on the incremental evolution of complexity within Genetic Programming, with an emphasis on understanding its effects on the Bloat phenomenon and local semantics


Summary While GP has proven itself to be a powerful and flexible problem solving tool, it still suffers from several shortcomings that limits its use and acceptance in some domains. In general, the most important drawback of GP is its inefficiencies, caused by the Bloat phenomenon and its reliance on representations with a low locality that make the search operators less effective.
In this work, we are proposing to abandon the focus of the traditional search based on fitness and semantics, and are instead focusing on program behavior and solution novelty