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+;;; org-learn.el --- Implements SuperMemo's incremental learning algorithm
+
+;; Copyright (C) 2009
+;;   Free Software Foundation, Inc.
+
+;; Author: John Wiegley <johnw at gnu dot org>
+;; Keywords: outlines, hypermedia, calendar, wp
+;; Homepage: http://orgmode.org
+;; Version: 6.32trans
+;;
+;; This file is part of GNU Emacs.
+;;
+;; GNU Emacs is free software: you can redistribute it and/or modify
+;; it under the terms of the GNU General Public License as published by
+;; the Free Software Foundation, either version 3 of the License, or
+;; (at your option) any later version.
+
+;; GNU Emacs is distributed in the hope that it will be useful,
+;; but WITHOUT ANY WARRANTY; without even the implied warranty of
+;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+;; GNU General Public License for more details.
+
+;; You should have received a copy of the GNU General Public License
+;; along with GNU Emacs.  If not, see <http://www.gnu.org/licenses/>.
+;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
+;;
+;;; Commentary:
+
+;; The file implements the learning algorithm described at
+;; http://supermemo.com/english/ol/sm5.htm, which is a system for reading
+;; material according to "spaced repetition".  See
+;; http://en.wikipedia.org/wiki/Spaced_repetition for more details.
+;;
+;; To use, turn on state logging and schedule some piece of information you
+;; want to read.  Then in the agenda buffer type
+
+(require 'org)
+(eval-when-compile
+  (require 'cl))
+
+(defgroup org-learn nil
+  "Options concerning the learning code in Org-mode."
+  :tag "Org Learn"
+  :group 'org-progress)
+
+(defcustom org-learn-always-reschedule nil
+  "If non-nil, always reschedule items, even if retention was \"perfect\"."
+  :type 'boolean
+  :group 'org-learn)
+
+(defcustom org-learn-fraction 0.5
+  "Controls the rate at which EF is increased or decreased.
+Must be a number between 0 and 1 (the greater it is the faster
+the changes of the OF matrix)."
+  :type 'float
+  :group 'org-learn)
+
+(defun initial-optimal-factor (n ef)
+  (if (= 1 n)
+      4
+    ef))
+
+(defun get-optimal-factor (n ef of-matrix)
+  (let ((factors (assoc n of-matrix)))
+    (or (and factors
+	     (let ((ef-of (assoc ef (cdr factors))))
+	       (and ef-of (cdr ef-of))))
+	(initial-optimal-factor n ef))))
+
+(defun set-optimal-factor (n ef of-matrix of)
+  (let ((factors (assoc n of-matrix)))
+    (if factors
+	(let ((ef-of (assoc ef (cdr factors))))
+	  (if ef-of
+	      (setcdr ef-of of)
+	    (push (cons ef of) (cdr factors))))
+      (push (cons n (list (cons ef of))) of-matrix)))
+  of-matrix)
+
+(defun inter-repetition-interval (n ef &optional of-matrix)
+  (let ((of (get-optimal-factor n ef of-matrix)))
+    (if (= 1 n)
+	of
+      (* of (inter-repetition-interval (1- n) ef of-matrix)))))
+
+(defun modify-e-factor (ef quality)
+  (if (< ef 1.3)
+      1.3
+    (+ ef (- 0.1 (* (- 5 quality) (+ 0.08 (* (- 5 quality) 0.02)))))))
+
+(defun modify-of (of q fraction)
+  (let ((temp (* of (+ 0.72 (* q 0.07)))))
+    (+ (* (- 1 fraction) of) (* fraction temp))))
+
+(defun calculate-new-optimal-factor (interval-used quality used-of
+						   old-of fraction)
+  "This implements the SM-5 learning algorithm in Lisp.
+INTERVAL-USED is the last interval used for the item in question.
+QUALITY is the quality of the repetition response.
+USED-OF is the optimal factor used in calculation of the last
+interval used for the item in question.
+OLD-OF is the previous value of the OF entry corresponding to the
+relevant repetition number and the E-Factor of the item.
+FRACTION is a number belonging to the range (0,1) determining the
+rate of modifications (the greater it is the faster the changes
+of the OF matrix).
+
+Returns the newly calculated value of the considered entry of the
+OF matrix."
+  (let (;; the value proposed for the modifier in case of q=5
+	(mod5 (/ (1+ interval-used) interval-used))
+	;; the value proposed for the modifier in case of q=2
+	(mod2 (/ (1- interval-used) interval-used))
+	;; the number determining how many times the OF value will
+	;; increase or decrease
+	modifier)
+    (if (< mod5 1.05)
+	(setq mod5 1.05))
+    (if (< mod2 0.75)
+	(setq mod5 0.75))
+    (if (> quality 4)
+	(setq modifier (1+ (* (- mod5 1) (- quality 4))))
+      (setq modifier (- 1 (* (/ (- 1 mod2) 2) (- 4 quality)))))
+    (if (< modifier 0.05)
+	(setq modifier 0.05))
+    (setq new-of (* used-of modifier))
+    (if (> quality 4)
+	(if (< new-of old-of)
+	    (setq new-of old-of)))
+    (if (< quality 4)
+	(if (> new-of old-of)
+	    (setq new-of old-of)))
+    (setq new-of (+ (* new-of fraction) (* old-of (- 1 fraction))))
+    (if (< new-of 1.2)
+	(setq new-of 1.2)
+      new-of)))
+
+(defvar initial-repetition-state '(-1 1 2.5 nil))
+
+(defun determine-next-interval (n ef quality of-matrix)
+  (assert (> n 0))
+  (assert (and (>= quality 0) (<= quality 5)))
+  (if (< quality 3)
+      (list (inter-repetition-interval n ef) (1+ n) ef nil)
+    (let ((next-ef (modify-e-factor ef quality)))
+      (setq of-matrix
+	    (set-optimal-factor n next-ef of-matrix
+				(modify-of (get-optimal-factor n ef of-matrix)
+					   quality org-learn-fraction))
+	    ef next-ef)
+      ;; For a zero-based quality of 4 or 5, don't repeat
+      (if (and (>= quality 4)
+	       (not org-learn-always-reschedule))
+	  (list 0 (1+ n) ef of-matrix)
+	(list (inter-repetition-interval n ef of-matrix) (1+ n)
+	      ef of-matrix)))))
+
+(defun org-smart-reschedule (quality)
+  (interactive "nHow well did you remember the information (on a scale of 0-5)? ")
+  (let* ((learn-str (org-entry-get (point) "LEARN_DATA"))
+	 (learn-data (or (and learn-str
+			      (read learn-str))
+			 (copy-list initial-repetition-state)))
+	 closed-dates)
+    (setq learn-data
+	  (determine-next-interval (nth 1 learn-data)
+				   (nth 2 learn-data)
+				   quality
+				   (nth 3 learn-data)))
+    (org-entry-put (point) "LEARN_DATA" (prin1-to-string learn-data))
+    (if (= 0 (nth 0 learn-data))
+	(org-schedule t)
+      (org-schedule nil (time-add (current-time)
+				  (days-to-time (nth 0 learn-data)))))))
+
+(provide 'org-learn)
+
+;; arch-tag: a46bb0e5-e4fb-4004-a9b8-63933c55af33
+
+;;; org-learn.el ends here