# HG changeset patch
# User Robert McIntyre <rlm@mit.edu>
# Date 1395886662 14400
# Node ID f339e3d5cc8cdf3a7ed8e4e27e59bc69c7dcb5df
# Parent  0a4362d1f1386b748ecd9716b12fb92f665f189f
finish draft of chapter 3.

diff -r 0a4362d1f138 -r f339e3d5cc8c org/self_organizing_touch.clj
--- a/org/self_organizing_touch.clj	Wed Mar 26 20:38:17 2014 -0400
+++ b/org/self_organizing_touch.clj	Wed Mar 26 22:17:42 2014 -0400
@@ -28,14 +28,14 @@
 
 (defn touch-kinesthetics []
   [[170 :lift-1 40]
-   [190 :lift-1 20]
+   [190 :lift-1 19]
    [206 :lift-1  0]
 
    [400 :lift-2 40]
    [410 :lift-2  0]
 
    [570 :lift-2 40]
-   [590 :lift-2 20]
+   [590 :lift-2 21]
    [606 :lift-2  0]
 
    [800 :lift-1 30]
@@ -57,10 +57,18 @@
 (defn single-worm-segment []
   (load-blender-model "Models/worm/worm-single-segment.blend"))
 
+(defn worm-segment []
+  (let [model (single-worm-segment)]
+    {:body (doto model (body!))
+     :touch (touch! model)
+     :proprioception (proprioception! model)
+     :muscles (movement! model)}))
+
+
 (defn worm-segment-defaults []
   (let [direct-control (worm-direct-control worm-muscle-labels 40)]
     (merge (worm-world-defaults)
-           {:worm-model single-worm-segment
+           {:worm worm-segment
             :view single-worm-segment-view
             :experience-watch nil
             :motor-control
@@ -97,23 +105,27 @@
    (rect-region [8   0] [14 29])
    (rect-region [15 15] [22 22])))
 
-(defn view-touch-region [coords]
-  (let [touched-region
-        (reduce
-         (fn [m k]
-           (assoc m k [0.0 0.1]))
-         (zipmap all-touch-coordinates (repeat [0.1 0.1])) coords)
-        data
-        [[(vec (keys touched-region)) (vec (vals touched-region))]]
-        touch-display (view-touch)]
-    (dorun (repeatedly 5 #(touch-display data)))))
+(defn view-touch-region
+  ([coords out]
+     (let [touched-region
+           (reduce
+            (fn [m k]
+              (assoc m k [0.0 0.1]))
+            (zipmap all-touch-coordinates (repeat [0.1 0.1])) coords)
+           data
+           [[(vec (keys touched-region)) (vec (vals touched-region))]]
+           touch-display (view-touch)]
+       (touch-display data out)))
+  ([coords] (view-touch-region nil)))
+
 
 (defn learn-touch-regions []
   (let [experiences (atom [])
         world (apply-map
                worm-world
                (assoc (worm-segment-defaults)
-                 :experiences experiences))]
+                 :experiences experiences
+                 :record (File. "/home/r/proj/cortex/thesis/video/touch-learn-2/")))]
     (run-world world)
     (->>
      @experiences
@@ -132,6 +144,24 @@
      (map set)
      remove-similar)))
 
+
+(def all-touch-coordinates
+  (concat
+   (rect-region [0  15] [7  22])
+   (rect-region [8   0] [14 29])
+   (rect-region [15 15] [22 22])))
+
+(defn view-touch-region [coords]
+  (let [touched-region
+        (reduce
+         (fn [m k]
+           (assoc m k [0.0 0.1]))
+         (zipmap all-touch-coordinates (repeat [0.1 0.1])) coords)
+        data
+        [[(vec (keys touched-region)) (vec (vals touched-region))]]
+        touch-display (view-touch)]
+    (dorun (repeatedly 5 #(touch-display data)))))
+
 (defn learn-and-view-touch-regions []
   (map view-touch-region
        (learn-touch-regions)))
diff -r 0a4362d1f138 -r f339e3d5cc8c thesis/cortex.org
--- a/thesis/cortex.org	Wed Mar 26 20:38:17 2014 -0400
+++ b/thesis/cortex.org	Wed Mar 26 22:17:42 2014 -0400
@@ -211,7 +211,8 @@
    #+caption: full circle. Imagine how you would replicate this functionality
    #+caption: using low-level pixel features such as HOG filters!
    #+name: grand-circle-intro
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn grand-circle?
   "Does the worm form a majestic circle (one end touching the other)?"
@@ -400,7 +401,7 @@
      :muscles (movement! model)}))
   #+end_src
   #+end_listing
-  
+
 ** Embodiment factors action recognition into managable parts
 
    Using empathy, I divide the problem of action recognition into a
@@ -436,7 +437,8 @@
    #+caption: independent and ignores vermopomorphic differences such as 
    #+caption: worm textures and colors.
    #+name: curled
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn curled?
   "Is the worm curled up?"
@@ -451,7 +453,9 @@
    #+caption: Program for summarizing the touch information in a patch 
    #+caption: of skin.
    #+name: touch-summary
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+
+#+begin_listing clojure
    #+begin_src clojure
 (defn contact
   "Determine how much contact a particular worm segment has with
@@ -476,7 +480,8 @@
    #+caption: floor. Note that this function contains no references to 
    #+caption: proprioction at all.
    #+name: resting
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (def worm-segment-bottom (rect-region [8 15] [14 22]))
 
@@ -495,7 +500,8 @@
    #+caption: I am able to both use a previous action predicate (=curled?=)
    #+caption: as well as the direct tactile experience of the head and tail.
    #+name: grand-circle
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (def worm-segment-bottom-tip (rect-region [15 15] [22 22]))
 
@@ -525,7 +531,8 @@
    #+caption: wiggle but can't. Frustrated wiggling is very visually different 
    #+caption: from actual wiggling, but this definition gives it to us for free.
    #+name: wiggling
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn fft [nums]
   (map
@@ -565,7 +572,8 @@
    #+caption: Use the action predicates defined earlier to report on 
    #+caption: what the worm is doing while in simulation.
    #+name: report-worm-activity
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn debug-experience
   [experiences text]
@@ -683,7 +691,8 @@
    #+caption: Program to convert an experience vector into a 
    #+caption: proprioceptively binned lookup function.
    #+name: bin
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn bin [digits]
   (fn [angles]
@@ -741,7 +750,8 @@
    #+caption: and finding the longest (ie. most coherent) interpretation
    #+caption: of the data.
    #+name: longest-thread
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn longest-thread
   "Find the longest thread from phi-index-sets. The index sets should
@@ -783,7 +793,8 @@
    #+caption: Fill in blanks in sensory experience by replicating the most 
    #+caption: recent experience.
    #+name: infer-nils
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn infer-nils
   "Replace nils with the next available non-nil element in the
@@ -804,19 +815,21 @@
    
    To use =EMPATH= with the worm, I first need to gather a set of
    experiences from the worm that includes the actions I want to
-   recognize. The =generate-phi-space= program (listint
+   recognize. The =generate-phi-space= program (listing
    \ref{generate-phi-space} runs the worm through a series of
    exercices and gatheres those experiences into a vector. The
    =do-all-the-things= program is a routine expressed in a simple
-   muscle contraction script language for automated worm control.
+   muscle contraction script language for automated worm control. It
+   causes the worm to rest, curl, and wiggle over about 700 frames
+   (approx. 11 seconds).
 
    #+caption: Program to gather the worm's experiences into a vector for 
    #+caption: further processing. The =motor-control-program= line uses
    #+caption: a motor control script that causes the worm to execute a series
    #+caption: of ``exercices'' that include all the action predicates.
    #+name: generate-phi-space
-   #+attr_latex: [!H]
-   #+begin_listing clojure 
+   #+attr_latex: [htpb]
+#+begin_listing clojure 
    #+begin_src clojure
 (def do-all-the-things 
   (concat
@@ -843,7 +856,8 @@
    #+caption: Use longest thread and a phi-space generated from a short
    #+caption: exercise routine to interpret actions during free play.
    #+name: empathy-debug
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (defn init []
   (def phi-space (generate-phi-space))
@@ -891,7 +905,8 @@
    #+caption: Determine how closely empathy approximates actual 
    #+caption: sensory data.
    #+name: test-empathy-accuracy
-   #+begin_listing clojure
+   #+attr_latex: [htpb]
+#+begin_listing clojure
    #+begin_src clojure
 (def worm-action-label
   (juxt grand-circle? curled? wiggling?))
@@ -931,6 +946,7 @@
 
    #+caption: Program to generate \Phi-space using manual training.
    #+name: manual-phi-space
+   #+attr_latex: [htpb]
    #+begin_listing clojure
    #+begin_src clojure
 (defn init-interactive []
@@ -949,11 +965,174 @@
 
   After about 1 minute of manual training, I was able to achieve 95%
   accuracy on manual testing of the worm using =init-interactive= and
-  =test-empathy-accuracy=. The ability of the system to infer sensory
-  states is truly impressive.
+  =test-empathy-accuracy=. The majority of errors are near the
+  boundaries of transitioning from one type of action to another.
+  During these transitions the exact label for the action is more open
+  to interpretation, and dissaggrement between empathy and experience
+  is more excusable.
 
 ** Digression: bootstrapping touch using free exploration
 
+   In the previous section I showed how to compute actions in terms of
+   body-centered predicates which relied averate touch activation of
+   pre-defined regions of the worm's skin. What if, instead of recieving
+   touch pre-grouped into the six faces of each worm segment, the true
+   topology of the worm's skin was unknown? This is more similiar to how
+   a nerve fiber bundle might be arranged. While two fibers that are
+   close in a nerve bundle /might/ correspond to two touch sensors that
+   are close together on the skin, the process of taking a complicated
+   surface and forcing it into essentially a circle requires some cuts
+   and rerragenments.
+   
+   In this section I show how to automatically learn the skin-topology of
+   a worm segment by free exploration. As the worm rolls around on the
+   floor, large sections of its surface get activated. If the worm has
+   stopped moving, then whatever region of skin that is touching the
+   floor is probably an important region, and should be recorded.
+   
+   #+caption: Program to detect whether the worm is in a resting state 
+   #+caption: with one face touching the floor.
+   #+name: pure-touch
+   #+begin_listing clojure
+   #+begin_src clojure
+(def full-contact [(float 0.0) (float 0.1)])
+
+(defn pure-touch?
+  "This is worm specific code to determine if a large region of touch
+   sensors is either all on or all off."
+  [[coords touch :as touch-data]]
+  (= (set (map first touch)) (set full-contact)))
+   #+end_src
+   #+end_listing
+
+   After collecting these important regions, there will many nearly
+   similiar touch regions. While for some purposes the subtle
+   differences between these regions will be important, for my
+   purposes I colapse them into mostly non-overlapping sets using
+   =remove-similiar= in listing \ref{remove-similiar}
+
+   #+caption: Program to take a lits of set of points and ``collapse them''
+   #+caption: so that the remaining sets in the list are siginificantly 
+   #+caption: different from each other. Prefer smaller sets to larger ones.
+   #+name: remove-similiar
+   #+begin_listing clojure
+   #+begin_src clojure
+(defn remove-similar
+  [coll]
+  (loop [result () coll (sort-by (comp - count) coll)]
+    (if (empty? coll) result
+        (let  [[x & xs] coll
+               c (count x)]
+          (if (some
+               (fn [other-set]
+                 (let [oc (count other-set)]
+                   (< (- (count (union other-set x)) c) (* oc 0.1))))
+               xs)
+            (recur result xs)
+            (recur (cons x result) xs))))))
+   #+end_src
+   #+end_listing
+
+   Actually running this simulation is easy given =CORTEX='s facilities.
+
+   #+caption: Collect experiences while the worm moves around. Filter the touch 
+   #+caption: sensations by stable ones, collapse similiar ones together, 
+   #+caption: and report the regions learned.
+   #+name: learn-touch
+   #+begin_listing clojure
+   #+begin_src clojure
+(defn learn-touch-regions []
+  (let [experiences (atom [])
+        world (apply-map
+               worm-world
+               (assoc (worm-segment-defaults)
+                 :experiences experiences))]
+    (run-world world)
+    (->>
+     @experiences
+     (drop 175)
+     ;; access the single segment's touch data
+     (map (comp first :touch))
+     ;; only deal with "pure" touch data to determine surfaces
+     (filter pure-touch?)
+     ;; associate coordinates with touch values
+     (map (partial apply zipmap))
+     ;; select those regions where contact is being made
+     (map (partial group-by second))
+     (map #(get % full-contact))
+     (map (partial map first))
+     ;; remove redundant/subset regions
+     (map set)
+     remove-similar)))
+
+(defn learn-and-view-touch-regions []
+  (map view-touch-region
+       (learn-touch-regions)))
+   #+end_src
+   #+end_listing
+
+   The only thing remining to define is the particular motion the worm
+   must take. I accomplish this with a simple motor control program.
+
+   #+caption: Motor control program for making the worm roll on the ground.
+   #+caption: This could also be replaced with random motion.
+   #+name: worm-roll
+   #+begin_listing clojure
+   #+begin_src clojure
+(defn touch-kinesthetics []
+  [[170 :lift-1 40]
+   [190 :lift-1 19]
+   [206 :lift-1  0]
+
+   [400 :lift-2 40]
+   [410 :lift-2  0]
+
+   [570 :lift-2 40]
+   [590 :lift-2 21]
+   [606 :lift-2  0]
+
+   [800 :lift-1 30]
+   [809 :lift-1 0]
+
+   [900 :roll-2 40]
+   [905 :roll-2 20]
+   [910 :roll-2  0]
+
+   [1000 :roll-2 40]
+   [1005 :roll-2 20]
+   [1010 :roll-2  0]
+   
+   [1100 :roll-2 40]
+   [1105 :roll-2 20]
+   [1110 :roll-2  0]
+   ])
+   #+end_src
+   #+end_listing
+
+
+   #+caption: The small worm rolls around on the floor, driven
+   #+caption: by the motor control program in listing \ref{worm-roll}.
+   #+name: worm-roll
+   #+ATTR_LaTeX: :width 12cm
+   [[./images/worm-roll.png]]
+
+
+   #+caption: After completing its adventures, the worm now knows 
+   #+caption: how its touch sensors are arranged along its skin. These 
+   #+caption: are the regions that were deemed important by 
+   #+caption: =learn-touch-regions=. Note that the worm has discovered
+   #+caption: that it has six sides.
+   #+name: worm-touch-map
+   #+ATTR_LaTeX: :width 12cm
+   [[./images/touch-learn.png]]
+
+   While simple, =learn-touch-regions= exploits regularities in both
+   the worm's physiology and the worm's environment to correctly
+   deduce that the worm has six sides. Note that =learn-touch-regions=
+   would work just as well even if the worm's touch sense data were
+   completely scrambled. The cross shape is just for convienence. This
+   example justifies the use of pre-defined touch regions in =EMPATH=.
+
 * Contributions
 
 
diff -r 0a4362d1f138 -r f339e3d5cc8c thesis/images/touch-learn.png
Binary file thesis/images/touch-learn.png has changed
diff -r 0a4362d1f138 -r f339e3d5cc8c thesis/images/worm-roll.png
Binary file thesis/images/worm-roll.png has changed
diff -r 0a4362d1f138 -r f339e3d5cc8c thesis/rlm-cortex-meng.tex
--- a/thesis/rlm-cortex-meng.tex	Wed Mar 26 20:38:17 2014 -0400
+++ b/thesis/rlm-cortex-meng.tex	Wed Mar 26 22:17:42 2014 -0400
@@ -45,6 +45,11 @@
 \usepackage{libertine}
 \usepackage{inconsolata}
 \usepackage{rotating}
+\usepackage{caption}
+
+%\usepackage{afterpage}
+
+%\afterpage{\clearpage}          %
 
 \usepackage[backend=bibtex,style=alphabetic]{biblatex}
 \addbibresource{cortex.bib}
@@ -58,6 +63,8 @@
     citecolor={dark-blue}, urlcolor={medium-blue}
 }
 
+\newenvironment{code}{\captionsetup{type=listing}}{}
+
 \renewcommand{\thesection}{\arabic{section}}
 \renewcommand{\thefigure}{\arabic{figure}}
 
@@ -82,6 +89,27 @@
 %\usepackage{lgrind}
 \pagestyle{plain}
 
+
+%% % Alter some LaTeX defaults for better treatment of figures:
+%% % See p.105 of "TeX Unbound" for suggested values.
+%% % See pp. 199-200 of Lamport's "LaTeX" book for details.
+%% %   General parameters, for ALL pages:
+%% \renewcommand{\topfraction}{0.9}	% max fraction of floats at top
+%% \renewcommand{\bottomfraction}{0.8}	% max fraction of floats at bottom
+%% %   Parameters for TEXT pages (not float pages):
+%% \setcounter{topnumber}{2}
+%% \setcounter{bottomnumber}{2}
+%% \setcounter{totalnumber}{4}     % 2 may work better
+%% \setcounter{dbltopnumber}{2}    % for 2-column pages
+%% \renewcommand{\dbltopfraction}{0.9}	% fit big float above 2-col. text
+%% \renewcommand{\textfraction}{0.07}	% allow minimal text w. figs
+%% %   Parameters for FLOAT pages (not text pages):
+%% \renewcommand{\floatpagefraction}{0.7}	% require fuller float pages
+%% % N.B.: floatpagefraction MUST be less than topfraction !!
+%% \renewcommand{\dblfloatpagefraction}{0.7}	% require fuller float pages
+%% % remember to use [htp] or [htpb] for placement
+
+
 \begin{document}
 
 \include{cover}