{"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/self-adaptive-surrogate-assisted-covariance","title":"Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy","arxiv_id":"1204.2356","date":"2012-04-11","proceeding":null,"authors":["Ilya Loshchilov","Marc Schoenauer","Michèle Sebag"],"abstract":"This paper presents a novel mechanism to adapt surrogate-assisted\npopulation-based algorithms. This mechanism is applied to ACM-ES, a recently\nproposed surrogate-assisted variant of CMA-ES. The resulting algorithm,\nsaACM-ES, adjusts online the lifelength of the current surrogate model (the\nnumber of CMA-ES generations before learning a new surrogate) and the surrogate\nhyper-parameters. Both heuristics significantly improve the quality of the\nsurrogate model, yielding a significant speed-up of saACM-ES compared to the\nACM-ES and CMA-ES baselines. The empirical validation of saACM-ES on the\nBBOB-2012 noiseless testbed demonstrates the efficiency and the scalability\nw.r.t the problem dimension and the population size of the proposed approach,\nthat reaches new best results on some of the benchmark problems.","url_abs":"http://arxiv.org/abs/1204.2356v1","url_pdf":"http://arxiv.org/pdf/1204.2356v1.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":"self-adaptive-surrogate-assisted-covariance","repo_url":"https://github.com/jyyang5/mu_mu_lambda-ES","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}