cortex: thesis/cortex.org comparison

comparison thesis/cortex.org @ 530:21b8389922ee

fix vermopomorphic footnote.

author	Robert McIntyre <rlm@mit.edu>
date	Sat, 26 Apr 2014 19:36:13 -0400
parents	96c189d4d15e
children	749452f063e5

comparison

equal deleted inserted replaced

-:96c189d4d15e
+:21b8389922ee
 #+name: name
 #+ATTR_LaTeX: :width 10cm
 [[./images/aurellem-gray.png]]
-* Empathy \& Embodiment: problem solving strategies
+* COMMENT Empathy \& Embodiment: problem solving strategies
 By the end of this thesis, you will have seen a novel approach to
 interpreting video using embodiment and empathy. You will also see
 one way to efficiently implement physical empathy for embodied
 creatures. Finally, you will become familiar with =CORTEX=, a system
 its own finger from the eye in its palm, and that it can feel its
 own thumb touching its palm.}
 \end{sidewaysfigure}
 #+END_LaTeX
-* Designing =CORTEX=
+* COMMENT Designing =CORTEX=
 In this section, I outline the design decisions that went into
 making =CORTEX=, along with some details about its implementation.
 (A practical guide to getting started with =CORTEX=, which skips
 over the history and implementation details presented here, is
 :proprioception (proprioception! model)
 :muscles (movement! model)}))
 #+end_src
 #+end_listing
-** Embodiment factors action recognition into manageable parts
+** COMMENT Embodiment factors action recognition into manageable parts
 Using empathy, I divide the problem of action recognition into a
 recognition process expressed in the language of a full compliment
 of senses, and an imaginative process that generates full sensory
 data from partial sensory data. Splitting the action recognition
 relies on proprioception, =resting?= relies on touch, =wiggling?=
 relies on a Fourier analysis of muscle contraction, and
 =grand-circle?= relies on touch and reuses =curled?= in its
 definition, showing how embodied predicates can be composed.
 #+caption: Program for detecting whether the worm is curled. This is the
 #+caption: simplest action predicate, because it only uses the last frame
 #+caption: of sensory experience, and only uses proprioceptive data. Even
 #+caption: this simple predicate, however, is automatically frame
-#+caption: independent and ignores vermopomorphic \begin{footnote} Like
+#+caption: independent and ignores vermopomorphic\protect\footnotemark
-#+caption: \emph{anthropomorphic}, except for worms instead of humans.
+#+caption: differences such as worm textures and colors.
-#+caption: \end{footnote} differences such as worm textures and colors.
 #+name: curled
 #+begin_listing clojure
 #+begin_src clojure
 (defn curled?
 "Is the worm curled up?"
 (fn [[_ _ bend]]
 (> (Math/sin bend) 0.64))
 (:proprioception (peek experiences))))
 #+end_src
 #+end_listing
+#+BEGIN_LaTeX
+\footnotetext{Like \emph{anthropomorphic} except for worms instead of humans.}
+#+END_LaTeX
 #+caption: Program for summarizing the touch information in a patch
 #+caption: of skin.
 #+name: touch-summary
 #+begin_listing clojure
 The trick now is to make the action predicates work even when the
 sensory data on which they depend is absent. If I can do that, then
 I will have gained much.
-** \Phi-space describes the worm's experiences
+** COMMENT \Phi-space describes the worm's experiences
 As a first step towards building empathy, I need to gather all of
 the worm's experiences during free play. I use a simple vector to
 store all the experiences.
 There is a simple way of taking \Phi-space and the total ordering
 provided by an experience vector and reliably inferring the rest of
 the senses.
-** Empathy is the process of tracing though \Phi-space
+** COMMENT Empathy is the process of tracing though \Phi-space
 Here is the core of a basic empathy algorithm, starting with an
 experience vector:
 First, group the experiences into tiered proprioceptive bins. I use
 (recur (dec i) (assoc! v (dec i) cur)))
 (recur i (assoc! v i 0))))))
 #+end_src
 #+end_listing
-** =EMPATH= recognizes actions efficiently
+** COMMENT =EMPATH= recognizes actions efficiently
 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 (listing
 \ref{generate-phi-space} runs the worm through a series of
 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 disagreement between empathy and experience
 is more excusable.
-** Digression: Learn touch sensor layout through free play
+** COMMENT Digression: Learn touch sensor layout through free play
 In the previous section I showed how to compute actions in terms of
 body-centered predicates which relied on the average touch
 activation of pre-defined regions of the worm's skin. What if,
 instead of receiving touch pre-grouped into the six faces of each
 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 convenience. This
 example justifies the use of pre-defined touch regions in =EMPATH=.
-* Contributions
+* COMMENT Contributions
 In this thesis you have seen the =CORTEX= system, a complete
 environment for creating simulated creatures. You have seen how to
 implement five senses: touch, proprioception, hearing, vision, and
 muscle tension. You have seen how to create new creatures using
 #+BEGIN_LaTeX
 \appendix
 #+END_LaTeX
-* Appendix: =CORTEX= User Guide
+* COMMENT Appendix: =CORTEX= User Guide
 Those who write a thesis should endeavor to make their code not only
 accessible, but actually usable, as a way to pay back the community
 that made the thesis possible in the first place. This thesis would
 not be possible without Free Software such as jMonkeyEngine3,

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comparison thesis/cortex.org @ 530:21b8389922ee