{"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/experiential-robot-learning-with-accelerated","title":"Experiential Robot Learning with Accelerated Neuroevolution","arxiv_id":"1808.05525","date":"2018-08-16","proceeding":null,"authors":["Ahmed Aly","Joanne B. Dugan"],"abstract":"Derivative-based optimization techniques such as Stochastic Gradient Descent\nhas been wildly successful in training deep neural networks. However, it has\nconstraints such as end-to-end network differentiability. As an alternative, we\npresent the Accelerated Neuroevolution algorithm. The new algorithm is aimed\ntowards physical robotic learning tasks following the Experiential Robot\nLearning method. We test our algorithm first on a simulated task of playing the\ngame Flappy Bird, then on a physical NAO robot in a static Object Centering\ntask. The agents successfully navigate the given tasks, in a relatively low\nnumber of generations. Based on our results, we propose to use the algorithm in\nmore complex tasks.","url_abs":"http://arxiv.org/abs/1808.05525v1","url_pdf":"http://arxiv.org/pdf/1808.05525v1.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":"experiential-robot-learning-with-accelerated","repo_url":"https://github.com/AroMorin/DNNOP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"navigate","task_name":"Navigate"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}