contrib/lisp/org-learn.el

   1 ;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
   2
   3 ;; Copyright (C) 2009-2012 Free Software Foundation, Inc.
   4
   5 ;; Author: John Wiegley <johnw at gnu dot org>
   6 ;; Keywords: outlines, hypermedia, calendar, wp
   7 ;; Homepage: http://orgmode.org
   8 ;; Version: 6.32trans
   9 ;;
  10 ;; This file is part of GNU Emacs.
  11 ;;
  12 ;; GNU Emacs is free software: you can redistribute it and/or modify
  13 ;; it under the terms of the GNU General Public License as published by
  14 ;; the Free Software Foundation, either version 3 of the License, or
  15 ;; (at your option) any later version.
  16
  17 ;; GNU Emacs is distributed in the hope that it will be useful,
  18 ;; but WITHOUT ANY WARRANTY; without even the implied warranty of
  19 ;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  20 ;; GNU General Public License for more details.
  21
  22 ;; You should have received a copy of the GNU General Public License
  23 ;; along with GNU Emacs.  If not, see <http://www.gnu.org/licenses/>.
  24 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
  25 ;;
  26 ;;; Commentary:
  27
  28 ;; The file implements the learning algorithm described at
  29 ;; http://supermemo.com/english/ol/sm5.htm, which is a system for reading
  30 ;; material according to "spaced repetition".  See
  31 ;; http://en.wikipedia.org/wiki/Spaced_repetition for more details.
  32 ;;
  33 ;; To use, turn on state logging and schedule some piece of information you
  34 ;; want to read.  Then in the agenda buffer type
  35
  36 (require 'org)
  37 (eval-when-compile
  38   (require 'cl))
  39
  40 (defgroup org-learn nil
  41   "Options concerning the learning code in Org-mode."
  42   :tag "Org Learn"
  43   :group 'org-progress)
  44
  45 (defcustom org-learn-always-reschedule nil
  46   "If non-nil, always reschedule items, even if retention was \"perfect\"."
  47   :type 'boolean
  48   :group 'org-learn)
  49
  50 (defcustom org-learn-fraction 0.5
  51   "Controls the rate at which EF is increased or decreased.
  52 Must be a number between 0 and 1 (the greater it is the faster
  53 the changes of the OF matrix)."
  54   :type 'float
  55   :group 'org-learn)
  56
  57 (defun initial-optimal-factor (n ef)
  58   (if (= 1 n)
  59       4
  60     ef))
  61
  62 (defun get-optimal-factor (n ef of-matrix)
  63   (let ((factors (assoc n of-matrix)))
  64     (or (and factors
  65              (let ((ef-of (assoc ef (cdr factors))))
  66                (and ef-of (cdr ef-of))))
  67         (initial-optimal-factor n ef))))
  68
  69 (defun set-optimal-factor (n ef of-matrix of)
  70   (let ((factors (assoc n of-matrix)))
  71     (if factors
  72         (let ((ef-of (assoc ef (cdr factors))))
  73           (if ef-of
  74               (setcdr ef-of of)
  75             (push (cons ef of) (cdr factors))))
  76       (push (cons n (list (cons ef of))) of-matrix)))
  77   of-matrix)
  78
  79 (defun inter-repetition-interval (n ef &optional of-matrix)
  80   (let ((of (get-optimal-factor n ef of-matrix)))
  81     (if (= 1 n)
  82         of
  83       (* of (inter-repetition-interval (1- n) ef of-matrix)))))
  84
  85 (defun modify-e-factor (ef quality)
  86   (if (< ef 1.3)
  87       1.3
  88     (+ ef (- 0.1 (* (- 5 quality) (+ 0.08 (* (- 5 quality) 0.02)))))))
  89
  90 (defun modify-of (of q fraction)
  91   (let ((temp (* of (+ 0.72 (* q 0.07)))))
  92     (+ (* (- 1 fraction) of) (* fraction temp))))
  93
  94 (defun calculate-new-optimal-factor (interval-used quality used-of
  95                                                    old-of fraction)
  96   "This implements the SM-5 learning algorithm in Lisp.
  97 INTERVAL-USED is the last interval used for the item in question.
  98 QUALITY is the quality of the repetition response.
  99 USED-OF is the optimal factor used in calculation of the last
 100 interval used for the item in question.
 101 OLD-OF is the previous value of the OF entry corresponding to the
 102 relevant repetition number and the E-Factor of the item.
 103 FRACTION is a number belonging to the range (0,1) determining the
 104 rate of modifications (the greater it is the faster the changes
 105 of the OF matrix).
 106
 107 Returns the newly calculated value of the considered entry of the
 108 OF matrix."
 109   (let (;; the value proposed for the modifier in case of q=5
 110         (mod5 (/ (1+ interval-used) interval-used))
 111         ;; the value proposed for the modifier in case of q=2
 112         (mod2 (/ (1- interval-used) interval-used))
 113         ;; the number determining how many times the OF value will
 114         ;; increase or decrease
 115         modifier)
 116     (if (< mod5 1.05)
 117         (setq mod5 1.05))
 118     (if (< mod2 0.75)
 119         (setq mod5 0.75))
 120     (if (> quality 4)
 121         (setq modifier (1+ (* (- mod5 1) (- quality 4))))
 122       (setq modifier (- 1 (* (/ (- 1 mod2) 2) (- 4 quality)))))
 123     (if (< modifier 0.05)
 124         (setq modifier 0.05))
 125     (setq new-of (* used-of modifier))
 126     (if (> quality 4)
 127         (if (< new-of old-of)
 128             (setq new-of old-of)))
 129     (if (< quality 4)
 130         (if (> new-of old-of)
 131             (setq new-of old-of)))
 132     (setq new-of (+ (* new-of fraction) (* old-of (- 1 fraction))))
 133     (if (< new-of 1.2)
 134         (setq new-of 1.2)
 135       new-of)))
 136
 137 (defvar initial-repetition-state '(-1 1 2.5 nil))
 138
 139 (defun determine-next-interval (n ef quality of-matrix)
 140   (assert (> n 0))
 141   (assert (and (>= quality 0) (<= quality 5)))
 142   (if (< quality 3)
 143       (list (inter-repetition-interval n ef) (1+ n) ef nil)
 144     (let ((next-ef (modify-e-factor ef quality)))
 145       (setq of-matrix
 146             (set-optimal-factor n next-ef of-matrix
 147                                 (modify-of (get-optimal-factor n ef of-matrix)
 148                                            quality org-learn-fraction))
 149             ef next-ef)
 150       ;; For a zero-based quality of 4 or 5, don't repeat
 151       (if (and (>= quality 4)
 152                (not org-learn-always-reschedule))
 153           (list 0 (1+ n) ef of-matrix)
 154         (list (inter-repetition-interval n ef of-matrix) (1+ n)
 155               ef of-matrix)))))
 156
 157 (defun org-smart-reschedule (quality)
 158   (interactive "nHow well did you remember the information (on a scale of 0-5)? ")
 159   (let* ((learn-str (org-entry-get (point) "LEARN_DATA"))
 160          (learn-data (or (and learn-str
 161                               (read learn-str))
 162                          (copy-list initial-repetition-state)))
 163          closed-dates)
 164     (setq learn-data
 165           (determine-next-interval (nth 1 learn-data)
 166                                    (nth 2 learn-data)
 167                                    quality
 168                                    (nth 3 learn-data)))
 169     (org-entry-put (point) "LEARN_DATA" (prin1-to-string learn-data))
 170     (if (= 0 (nth 0 learn-data))
 171         (org-schedule t)
 172       (org-schedule nil (time-add (current-time)
 173                                   (days-to-time (nth 0 learn-data)))))))
 174
 175 (provide 'org-learn)
 176
 177 ;;; org-learn.el ends here