A learning algorithm is a formula that determines when a note or flashcard should next be reviewed.
+| Algorithm | +Status | +
|---|---|
| SM-2-OSR | +Implemented | +
| FSRS | +Planned | +
| User Defined Intervals | +Planned | +
SM-2-OSR algorithm is a variant of Anki's algorithm which is based on the SM-2 algorithm.Warning
+Note that this hasn't been updated in a while, +please see the code.
+if link_count > 0: initial_ease = (1 - link_contribution) * base_ease + link_contribution * average_ease - link_contribution = max_link_factor * min(1.0, log(link_count + 0.5) / log(64)) (cater for uncertainty)20 and the interval changes to old_interval * new_ease / 100 * 1.3 (the 1.3 is the easy bonus)old_interval * old_ease / 10020 and the interval changes to old_interval * 0.50.5 can be modified in settingsminimum ease = 1308 or more days:interval += random_choice({-fuzz, 0, +fuzz})fuzz = ceil(0.05 * interval)The algorithm is detailed at: +fsrs4anki
+Incorporation of the FSRS algorithm into this plugin has not yet occurred. For progress see: + [FEAT] sm-2 is outdated, can you please replace it with the fsrs algorithm? #748
+This is the simplest "algorithm" possible. There are fixed intervals configured by the user for each of the possible review outcomes.
+For example, hard might be configured for an interval of 1 day.
Implementation of this technique has not yet occurred. For progress see: + [FEAT] user defined "Easy, Good, Hard" values instead of or in addition to the algorithm defined one. #741
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