{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/semantic-variation-operators-for","title":"Semantic variation operators for multidimensional genetic programming","arxiv_id":"1904.08577","date":"2019-04-18","proceeding":null,"authors":["William La Cava","Jason H. Moore"],"abstract":"Multidimensional genetic programming represents candidate solutions as sets\nof programs, and thereby provides an interesting framework for exploiting\nbuilding block identification. Towards this goal, we investigate the use of\nmachine learning as a way to bias which components of programs are promoted,\nand propose two semantic operators to choose where useful building blocks are\nplaced during crossover. A forward stagewise crossover operator we propose\nleads to significant improvements on a set of regression problems, and produces\nstate-of-the-art results in a large benchmark study. We discuss this\narchitecture and others in terms of their propensity for allowing heuristic\nsearch to utilize information during the evolutionary process. Finally, we look\nat the collinearity and complexity of the data representations that result from\nthese architectures, with a view towards disentangling factors of variation in\napplication.","url_abs":"http://arxiv.org/abs/1904.08577v1","url_pdf":"http://arxiv.org/pdf/1904.08577v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"semantic-variation-operators-for","repo_url":"https://github.com/lacava/gecco_2019","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"heuristic-search","task_name":"Heuristic Search"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}