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authorTerrence Brannon <metaperl@gmail.com>2018-12-07 22:02:54 +0000
committerEli Zaretskii <eliz@gnu.org>2018-12-22 12:46:15 +0200
commit85516b8cc8a6c5767ab29917556f5b30b4482b73 (patch)
tree215fd0cbb5d0386c4d6c52549590f279e4929aa7
parent081fb694c3f88e77d4a0e09fba8ce457037b9132 (diff)
downloademacs-85516b8cc8a6c5767ab29917556f5b30b4482b73.tar.gz
Minor copyedits in landmark.el
* lisp/obsolete/landmark.el: Fix author's email and commentary.
-rw-r--r--lisp/obsolete/landmark.el11
1 files changed, 9 insertions, 2 deletions
diff --git a/lisp/obsolete/landmark.el b/lisp/obsolete/landmark.el
index effea95cd8f..c4c4c7a20f6 100644
--- a/lisp/obsolete/landmark.el
+++ b/lisp/obsolete/landmark.el
@@ -2,7 +2,7 @@
;; Copyright (C) 1996-1997, 2000-2018 Free Software Foundation, Inc.
-;; Author: Terrence Brannon (was: <brannon@rana.usc.edu>)
+;; Author: Terrence Brannon <metaperl@gmail.com>
;; Created: December 16, 1996 - first release to usenet
;; Keywords: games, neural network, adaptive search, chemotaxis
;; Version: 1.0
@@ -36,7 +36,7 @@
;; the smell of the tree increases, then the weights in the robot's
;; brain are adjusted to encourage this odor-driven behavior in the
;; future. If the smell of the tree decreases, the robots weights are
-;; adjusted to discourage a correct move.
+;; adjusted to discourage that odor-driven behavior.
;; In laymen's terms, the search space is initially flat. The point
;; of training is to "turn up the edges of the search space" so that
@@ -53,6 +53,13 @@
;; a single move, one moves east,west and south, then both east and
;; west will be improved when they shouldn't
+;; The source code was developed as part of a course on Brain Theory
+;; and Neural Networks at the University of Southern California. The
+;; original problem description and solution appeared in 1981 in the
+;; paper "Landmark Learning: An Illustration of Associative
+;; Search" authored by Andrew G. Barto and Richard S. Sutton and
+;; published to Biological Cybernetics.
+
;; Many thanks to Yuri Pryadkin <yuri@rana.usc.edu> for this
;; concise problem description.