{"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/hyper-parameter-sweep-on-alphazero-general","title":"Hyper-Parameter Sweep on AlphaZero General","arxiv_id":"1903.08129","date":"2019-03-19","proceeding":null,"authors":["Hui Wang","Michael Emmerich","Mike Preuss","Aske Plaat"],"abstract":"Since AlphaGo and AlphaGo Zero have achieved breakground successes in the\ngame of Go, the programs have been generalized to solve other tasks.\nSubsequently, AlphaZero was developed to play Go, Chess and Shogi. In the\nliterature, the algorithms are explained well. However, AlphaZero contains many\nparameters, and for neither AlphaGo, AlphaGo Zero nor AlphaZero, there is\nsufficient discussion about how to set parameter values in these algorithms.\nTherefore, in this paper, we choose 12 parameters in AlphaZero and evaluate how\nthese parameters contribute to training. We focus on three objectives~(training\nloss, time cost and playing strength). For each parameter, we train 3 models\nusing 3 different values~(minimum value, default value, maximum value). We use\nthe game of play 6$\\times$6 Othello, on the AlphaZeroGeneral open source\nre-implementation of AlphaZero. Overall, experimental results show that\ndifferent values can lead to different training results, proving the importance\nof such a parameter sweep. We categorize these 12 parameters into\ntime-sensitive parameters and time-friendly parameters. Moreover, through\nmulti-objective analysis, this paper provides an insightful basis for further\nhyper-parameter optimization.","url_abs":"http://arxiv.org/abs/1903.08129v1","url_pdf":"http://arxiv.org/pdf/1903.08129v1.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":"hyper-parameter-sweep-on-alphazero-general","repo_url":"https://github.com/QueensGambit/CrazyAra","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mxnet","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"game-of-go","task_name":"Game of Go"}],"methods":[{"method_slug":"alphazero","method_name":"AlphaZero"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1903.08129","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}