Editing Spaced repetition (section)

==Algorithms==
There are several families of spaced repetition algorithms:

* [[Leitner system]] – a simple scheme that uses five levels and an arbitrary number of study stages
* [[Neural network (machine learning)|Neural-network-based]]<ref>{{Cite web |last1=Dreger |first1=Bartosz |last2=Wozniak |first2=Piotr |url=https://www.supermemo.com/en/archives1990-2015/english/ol/nn_train |title=Implementing a neural network for repetition spacing |website=www.supermemo.com |archive-url=https://web.archive.org/web/20220821061451/https://www.supermemo.com/en/archives1990-2015/english/ol/nn_train |access-date=July 15, 2017|archive-date=August 21, 2022 }}</ref><ref>{{cite arXiv |last=Balepur |first=Nishant |date=2024-02-19 |title=KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students |class=cs.CL |eprint=2402.12291}}</ref>
* The SM family of algorithms ([[SuperMemo#Algorithms]]), ranging from SM-0 (a paper-and-pencil prototype) to SM-18,<ref>{{Cite web |title=Algorithm SM-18 |url=https://supermemo.guru/wiki/Algorithm_SM-18 |website=www.supermemo.guru |url-status=live |archive-url=https://web.archive.org/web/20240313020019/https://supermemo.guru/wiki/Algorithm_SM-18 |archive-date=2024-03-13 |last=Wozniak |first=Piotr |date=2019-05-02}}</ref> which is built into SuperMemo 18 and 19.
* The DASH<ref>{{cite thesis |last=Lindsey |first=Robert Victor |date=2014 |title=Probabilistic Models of Student Learning and Forgetting |url=https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/zp38wc97m |institution=University of Colorado Boulder |type=Master’s thesis}}</ref><ref>{{cite thesis |last=Randazzo |first=Giacomo |date=2022-04-28 |title=Memory Models for Spaced Repetition Systems |hdl=10589/186407 |url-status=live |url=https://hdl.handle.net/10589/186407 |institution=Politecnico di Milano |type=Master’s thesis}}</ref> (''Difficulty, Ability and Study History'') family
* SSP-MMC<ref>{{Cite web |last=Ye |first=Junyao |date=2023-11-13 |title=Spaced Repetition Algorithm: A Three-Day Journey from Novice to Expert |url=https://github.com/open-spaced-repetition/fsrs4anki/wiki/Spaced-Repetition-Algorithm:-A-Three%E2%80%90Day-Journey-from-Novice-to-Expert |url-status=live |archive-url=https://web.archive.org/web/20231113115450/https://github.com/open-spaced-repetition/fsrs4anki/wiki/Spaced-Repetition-Algorithm:-A-Three%E2%80%90Day-Journey-from-Novice-to-Expert |archive-date=2023-11-13 |access-date=2023-11-14 |website=[[GitHub]]}}</ref><ref>{{Cite conference |last1=Ye |first1=Junyao |last2=Su |first2=Jingyong |last3=Cao |first3=Yilong |chapter=A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling |date=2022-08-14 |title=Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining |series=KDD '22 |location=New York, NY, USA |publisher=Association for Computing Machinery |pages=4381–4390 |doi=10.1145/3534678.3539081 |isbn=978-1-4503-9385-0|s2cid=251518206 }}</ref><ref>{{Cite journal |last1=Ye |first1=Junyao |last2=Su |first2=Jingyong |last3=Nie |first3=Liqiang |last4=Cao |first4=Yilong |last5=Chen |first5=Yongyong |title=Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory |date=2023-10-01 |journal=IEEE Transactions on Knowledge and Data Engineering |volume=35 |issue=10 |pages=10085–10097 |doi=10.1109/TKDE.2023.3251721}}</ref> (''Stochastic Shortest Path Minimize Memorization Cost'') and the closely related FSRS<ref>{{Cite web |last=Ye |first=Junyao |date=2023-11-06 |title=fsrs4anki |url=https://github.com/open-spaced-repetition/fsrs4anki/blob/a9bf76eb05ac946e4b4dab5700d42d384dd82101/README.md |url-status=live |archive-url=https://web.archive.org/web/20230619004223/https://github.com/open-spaced-repetition/fsrs4anki/blob/main/README.md |archive-date=2023-06-19 |access-date=2023-11-14 |website=[[GitHub]]}}</ref> (''Free Spaced Repetition Scheduler''), which is available in Anki starting with release 23.10<ref>{{Cite web |last=Damien |first=Elmes |date=2023-10-31 |title=Anki Release 23.10 |url=https://github.com/ankitects/anki/releases/tag/23.10 |url-status=live |archive-url=https://web.archive.org/web/20231103204635/https://github.com/ankitects/anki/releases/tag/23.10 |archive-date=2023-11-03 |access-date=2023-11-14 |website=[[GitHub]] |publisher=GitHub}}</ref> and in RemNote starting with release 1.16<ref>{{Cite web |date=2024-04-23 |title=RemNote Release 1.16 |url=https://feedback.remnote.com/changelog/remnote-1-16-ultimate-spaced-repetition |access-date=2024-04-25 }}</ref>