contrib/lisp/org-learn.el

   1 ;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
   2
   3 ;; Copyright (C) 2009
   4 ;;   Free Software Foundation, Inc.
   5
   6 ;; Author: John Wiegley <johnw at gnu dot org>
   7 ;; Keywords: outlines, hypermedia, calendar, wp
   8 ;; Homepage: http://orgmode.org
   9 ;; Version: 6.32trans
  10 ;;
  11 ;; This file is part of GNU Emacs.
  12 ;;
  13 ;; GNU Emacs is free software: you can redistribute it and/or modify
  14 ;; it under the terms of the GNU General Public License as published by
  15 ;; the Free Software Foundation, either version 3 of the License, or
  16 ;; (at your option) any later version.
  17
  18 ;; GNU Emacs is distributed in the hope that it will be useful,
  19 ;; but WITHOUT ANY WARRANTY; without even the implied warranty of
  20 ;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  21 ;; GNU General Public License for more details.
  22
  23 ;; You should have received a copy of the GNU General Public License
  24 ;; along with GNU Emacs.  If not, see <http://www.gnu.org/licenses/>.
  25 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
  26 ;;
  27 ;;; Commentary:
  28
  29 ;; The file implements the learning algorithm described at
  30 ;; http://supermemo.com/english/ol/sm5.htm, which is a system for reading
  31 ;; material according to "spaced repetition".  See
  32 ;; http://en.wikipedia.org/wiki/Spaced_repetition for more details.
  33 ;;
  34 ;; To use, turn on state logging and schedule some piece of information you
  35 ;; want to read.  Then in the agenda buffer type
  36
  37 (require 'org)
  38 (eval-when-compile
  39   (require 'cl))
  40
  41 (defgroup org-learn nil
  42   "Options concerning the learning code in Org-mode."
  43   :tag "Org Learn"
  44   :group 'org-progress)
  45
  46 (defcustom org-learn-always-reschedule nil
  47   "If non-nil, always reschedule items, even if retention was \"perfect\"."
  48   :type 'boolean
  49   :group 'org-learn)
  50
  51 (defcustom org-learn-fraction 0.5
  52   "Controls the rate at which EF is increased or decreased.
  53 Must be a number between 0 and 1 (the greater it is the faster
  54 the changes of the OF matrix)."
  55   :type 'float
  56   :group 'org-learn)
  57
  58 (defun initial-optimal-factor (n ef)
  59   (if (= 1 n)
  60       4
  61     ef))
  62
  63 (defun get-optimal-factor (n ef of-matrix)
  64   (let ((factors (assoc n of-matrix)))
  65     (or (and factors
  66              (let ((ef-of (assoc ef (cdr factors))))
  67                (and ef-of (cdr ef-of))))
  68         (initial-optimal-factor n ef))))
  69
  70 (defun set-optimal-factor (n ef of-matrix of)
  71   (let ((factors (assoc n of-matrix)))
  72     (if factors
  73         (let ((ef-of (assoc ef (cdr factors))))
  74           (if ef-of
  75               (setcdr ef-of of)
  76             (push (cons ef of) (cdr factors))))
  77       (push (cons n (list (cons ef of))) of-matrix)))
  78   of-matrix)
  79
  80 (defun inter-repetition-interval (n ef &optional of-matrix)
  81   (let ((of (get-optimal-factor n ef of-matrix)))
  82     (if (= 1 n)
  83         of
  84       (* of (inter-repetition-interval (1- n) ef of-matrix)))))
  85
  86 (defun modify-e-factor (ef quality)
  87   (if (< ef 1.3)
  88       1.3
  89     (+ ef (- 0.1 (* (- 5 quality) (+ 0.08 (* (- 5 quality) 0.02)))))))
  90
  91 (defun modify-of (of q fraction)
  92   (let ((temp (* of (+ 0.72 (* q 0.07)))))
  93     (+ (* (- 1 fraction) of) (* fraction temp))))
  94
  95 (defun calculate-new-optimal-factor (interval-used quality used-of
  96                                                    old-of fraction)
  97   "This implements the SM-5 learning algorithm in Lisp.
  98 INTERVAL-USED is the last interval used for the item in question.
  99 QUALITY is the quality of the repetition response.
 100 USED-OF is the optimal factor used in calculation of the last
 101 interval used for the item in question.
 102 OLD-OF is the previous value of the OF entry corresponding to the
 103 relevant repetition number and the E-Factor of the item.
 104 FRACTION is a number belonging to the range (0,1) determining the
 105 rate of modifications (the greater it is the faster the changes
 106 of the OF matrix).
 107
 108 Returns the newly calculated value of the considered entry of the
 109 OF matrix."
 110   (let (;; the value proposed for the modifier in case of q=5
 111         (mod5 (/ (1+ interval-used) interval-used))
 112         ;; the value proposed for the modifier in case of q=2
 113         (mod2 (/ (1- interval-used) interval-used))
 114         ;; the number determining how many times the OF value will
 115         ;; increase or decrease
 116         modifier)
 117     (if (< mod5 1.05)
 118         (setq mod5 1.05))
 119     (if (< mod2 0.75)
 120         (setq mod5 0.75))
 121     (if (> quality 4)
 122         (setq modifier (1+ (* (- mod5 1) (- quality 4))))
 123       (setq modifier (- 1 (* (/ (- 1 mod2) 2) (- 4 quality)))))
 124     (if (< modifier 0.05)
 125         (setq modifier 0.05))
 126     (setq new-of (* used-of modifier))
 127     (if (> quality 4)
 128         (if (< new-of old-of)
 129             (setq new-of old-of)))
 130     (if (< quality 4)
 131         (if (> new-of old-of)
 132             (setq new-of old-of)))
 133     (setq new-of (+ (* new-of fraction) (* old-of (- 1 fraction))))
 134     (if (< new-of 1.2)
 135         (setq new-of 1.2)
 136       new-of)))
 137
 138 (defvar initial-repetition-state '(-1 1 2.5 nil))
 139
 140 (defun determine-next-interval (n ef quality of-matrix)
 141   (assert (> n 0))
 142   (assert (and (>= quality 0) (<= quality 5)))
 143   (if (< quality 3)
 144       (list (inter-repetition-interval n ef) (1+ n) ef nil)
 145     (let ((next-ef (modify-e-factor ef quality)))
 146       (setq of-matrix
 147             (set-optimal-factor n next-ef of-matrix
 148                                 (modify-of (get-optimal-factor n ef of-matrix)
 149                                            quality org-learn-fraction))
 150             ef next-ef)
 151       ;; For a zero-based quality of 4 or 5, don't repeat
 152       (if (and (>= quality 4)
 153                (not org-learn-always-reschedule))
 154           (list 0 (1+ n) ef of-matrix)
 155         (list (inter-repetition-interval n ef of-matrix) (1+ n)
 156               ef of-matrix)))))
 157
 158 (defun org-smart-reschedule (quality)
 159   (interactive "nHow well did you remember the information (on a scale of 0-5)? ")
 160   (let* ((learn-str (org-entry-get (point) "LEARN_DATA"))
 161          (learn-data (or (and learn-str
 162                               (read learn-str))
 163                          (copy-list initial-repetition-state)))
 164          closed-dates)
 165     (setq learn-data
 166           (determine-next-interval (nth 1 learn-data)
 167                                    (nth 2 learn-data)
 168                                    quality
 169                                    (nth 3 learn-data)))
 170     (org-entry-put (point) "LEARN_DATA" (prin1-to-string learn-data))
 171     (if (= 0 (nth 0 learn-data))
 172         (org-schedule t)
 173       (org-schedule nil (time-add (current-time)
 174                                   (days-to-time (nth 0 learn-data)))))))
 175
 176 (provide 'org-learn)
 177
 178 ;; arch-tag: a46bb0e5-e4fb-4004-a9b8-63933c55af33
 179
 180 ;;; org-learn.el ends here