{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:18:18Z","timestamp":1761175098613,"version":"build-2065373602"},"reference-count":10,"publisher":"Polish Information Processing Society","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.15439\/2025f6771","type":"proceedings-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T07:44:23Z","timestamp":1761119063000},"page":"837-842","source":"Crossref","is-referenced-by-count":1,"title":["The bread emoji Team\u2019s Submission to the 2025 FedCSIS Predicting Chess Puzzle Difficulty Challenge"],"prefix":"10.15439","volume":"43","author":[{"given":"Tyler","family":"Woodruff","sequence":"first","affiliation":[{"name":"Amazon"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luke","family":"Imbing","sequence":"additional","affiliation":[{"name":"Independent Researcher"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Cognetta","sequence":"additional","affiliation":[{"name":"Institute of Science Tokyo"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"6175","published-online":{"date-parts":[[2025,10,15]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","unstructured":"J. Zy\u015bko, M. \u015al\u0229zak, D. \u015al\u0229zak, and M. \u015awiechowski,\n\u201cFedCSIS 2025 knowledgepit.ai Competition: Predicting\nChess Puzzle Difficulty Part 2 & A Step Toward\nUncertainty Contests,\u201d in Proceedings of the 20th\nConference on Computer Science and Intelligence\nSystems, ser. Annals of Computer Science and\nInformation Systems, M. Bolanowski, M. Ganzha,\nL. Maciaszek, M. Paprzycki, and D. \u015al\u0229zak, Eds., vol. 43.\nPolish Information Processing Society, 2025. [Online].\nAvailable: http:\/\/dx.doi.org\/10.15439\/2025F5937","DOI":"10.15439\/2025F5937"},{"key":"ref2","unstructured":"M. E. Glickman, \u201cExample of the glicko-2 system,\u201d http:\/\/www.glicko.net\/glicko\/glicko2.pdf, 2022."},{"key":"ref3","doi-asserted-by":"crossref","unstructured":"T. Woodruff, O. Filatov, and M. Cognetta, \u201cThe bread\nemoji team\u2019s submission to the ieee bigdata 2024 cup:\nPredicting chess puzzle difficulty challenge,\u201d in 2024\nIEEE International Conference on Big Data (BigData),\n2024, pp. 8415\u20138422.","DOI":"10.1109\/BigData62323.2024.10826037"},{"key":"ref4","doi-asserted-by":"crossref","unstructured":"J. Zy\u015bko, M. \u015awiechowski, S. Stawicki, K. Jagie\u0142a,\nA. Janusz, and D. \u015al\u0229zak, \u201cIeee big data cup 2024 report:\nPredicting chess puzzle difficulty at knowledgepit.ai,\u201d in\nIEEE International Conference on Big Data, Big Data\n2024, Washington DC, USA, December 15-18, 2024.\nIEEE, 2024.","DOI":"10.1109\/BigData62323.2024.10825289"},{"key":"ref5","unstructured":"D. Klein, \u201cNeural networks for chess,\u201d 2022. [Online].\nAvailable: https:\/\/arxiv.org\/abs\/2209.01506"},{"key":"ref6","doi-asserted-by":"publisher","unstructured":"R. McIlroy-Young, S. Sen, J. M. Kleinberg, and\nA. Anderson, \u201cAligning superhuman AI with human\nbehavior: Chess as a model system,\u201d in KDD \u201920:\nThe 26th ACM SIGKDD Conference on Knowledge\nDiscovery and Data Mining, Virtual Event, CA, USA,\nAugust 23-27, 2020, R. Gupta, Y. Liu, J. Tang, and B. A.\nPrakash, Eds. ACM, 2020, pp. 1677\u20131687. [Online].\nAvailable: https:\/\/doi.org\/10.1145\/3394486.3403219","DOI":"10.1145\/3394486.3403219"},{"key":"ref7","unstructured":"Z. Tang, D. Jiao, R. McIlroy-Young, J. Kleinberg,\nS. Sen, and A. Anderson, \u201cMaia-2: A unified model for\nhuman-ai alignment in chess,\u201d 2024. [Online]. Available:\nhttps:\/\/arxiv.org\/abs\/2409.20553"},{"key":"ref8","unstructured":"T. L. Authors, \u201cLeela chess zero,\u201d https:\/\/lczero.org\/."},{"key":"ref9","unstructured":"D. Silver, T. Hubert, J. Schrittwieser, I. Antonoglou,\nM. Lai, A. Guez, M. Lanctot, L. Sifre, D. Kumaran,\nT. Graepel, T. Lillicrap, K. Simonyan, and D. Hassabis,\n\u201cMastering chess and shogi by self-play with a general\nreinforcement learning algorithm,\u201d 2017. [Online].\nAvailable: https:\/\/arxiv.org\/abs\/1712.01815"},{"key":"ref10","doi-asserted-by":"crossref","unstructured":"S. Bj\u00f6rkqvist, \u201cEstimating the puzzlingness of chess\npuzzles,\u201d in 2024 IEEE International Conference on Big\nData (BigData), 2024, pp. 8370\u20138376.","DOI":"10.1109\/BigData62323.2024.10825991"}],"event":{"name":"20th Conference on Computer Science and Intelligence Systems (FedCSIS)","theme":"Computer Science and Intelligence Systems","location":"Krak\u00f3w, Poland","acronym":"FedCSIS","number":"20","start":{"date-parts":[[2025,9,14]]},"end":{"date-parts":[[2025,9,17]]}},"container-title":["Annals of Computer Science and Information Systems","Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS)"],"original-title":[],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T07:52:16Z","timestamp":1761119536000},"score":1,"resource":{"primary":{"URL":"https:\/\/annals-csis.org\/Volume_43\/drp\/6771.html"}},"subtitle":[],"proceedings-subject":"Computer Science and Information Systems","short-title":[],"issued":{"date-parts":[[2025,10,15]]},"references-count":10,"URL":"https:\/\/doi.org\/10.15439\/2025f6771","relation":{},"ISSN":["2300-5963"],"issn-type":[{"value":"2300-5963","type":"print"}],"subject":[],"published":{"date-parts":[[2025,10,15]]}}}