Mercurial > cortex
changeset 545:b2c66ea58c39
changes from athena.
author | Robert McIntyre <rlm@mit.edu> |
---|---|
date | Mon, 28 Apr 2014 12:59:08 -0400 |
parents | 431e6aedf67d |
children | f4770e3d30ae |
files | thesis/cortex.org |
diffstat | 1 files changed, 8 insertions(+), 6 deletions(-) [+] |
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1.1 --- a/thesis/cortex.org Mon Apr 28 01:06:03 2014 -0400 1.2 +++ b/thesis/cortex.org Mon Apr 28 12:59:08 2014 -0400 1.3 @@ -349,7 +349,7 @@ 1.4 1.5 - =CORTEX= implements a wide variety of senses: touch, 1.6 proprioception, vision, hearing, and muscle tension. Complicated 1.7 - senses like touch, and vision involve multiple sensory elements 1.8 + senses like touch and vision involve multiple sensory elements 1.9 embedded in a 2D surface. You have complete control over the 1.10 distribution of these sensor elements through the use of simple 1.11 png image files. In particular, =CORTEX= implements more 1.12 @@ -1132,6 +1132,7 @@ 1.13 #+caption: with =bind-sense= 1.14 #+name: add-eye 1.15 #+begin_listing clojure 1.16 + #+begin_src clojure 1.17 (defn add-eye! 1.18 "Create a Camera centered on the current position of 'eye which 1.19 follows the closest physical node in 'creature. The camera will 1.20 @@ -1157,6 +1158,7 @@ 1.21 (float 1) 1.22 (float 1000)) 1.23 (bind-sense target cam) cam)) 1.24 + #+end_src 1.25 #+end_listing 1.26 1.27 *** Simulated Retina 1.28 @@ -1191,8 +1193,8 @@ 1.29 #+ATTR_LaTeX: :width 7cm 1.30 [[./images/retina-small.png]] 1.31 1.32 - Together, the number 0xFF0000 and the image image above describe 1.33 - the placement of red-sensitive sensory elements. 1.34 + Together, the number 0xFF0000 and the image above describe the 1.35 + placement of red-sensitive sensory elements. 1.36 1.37 Meta-data to very crudely approximate a human eye might be 1.38 something like this: 1.39 @@ -2179,7 +2181,7 @@ 1.40 *** Proprioception Kernel 1.41 1.42 Given a joint, =proprioception-kernel= produces a function that 1.43 - calculates the Euler angles between the the objects the joint 1.44 + calculates the Euler angles between the objects the joint 1.45 connects. The only tricky part here is making the angles relative 1.46 to the joint's initial ``straightness''. 1.47 1.48 @@ -2559,7 +2561,7 @@ 1.49 ** Action recognition is easy with a full gamut of senses 1.50 1.51 Embodied representations using multiple senses such as touch, 1.52 - proprioception, and muscle tension turns out be be exceedingly 1.53 + proprioception, and muscle tension turns out be exceedingly 1.54 efficient at describing body-centered actions. It is the right 1.55 language for the job. For example, it takes only around 5 lines of 1.56 LISP code to describe the action of curling using embodied 1.57 @@ -3049,7 +3051,7 @@ 1.58 experiences from the worm that includes the actions I want to 1.59 recognize. The =generate-phi-space= program (listing 1.60 \ref{generate-phi-space} runs the worm through a series of 1.61 - exercises and gatherers those experiences into a vector. The 1.62 + exercises and gathers those experiences into a vector. The 1.63 =do-all-the-things= program is a routine expressed in a simple 1.64 muscle contraction script language for automated worm control. It 1.65 causes the worm to rest, curl, and wiggle over about 700 frames