diff thesis/abstract.org @ 436:853377051f1e

abstract v. 2
author Robert McIntyre <rlm@mit.edu>
date Sun, 23 Mar 2014 19:09:14 -0400
parents ae3bfc82ac7c
children c1e6b7221b2f
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     1.1 --- a/thesis/abstract.org	Sun Mar 23 17:59:16 2014 -0400
     1.2 +++ b/thesis/abstract.org	Sun Mar 23 19:09:14 2014 -0400
     1.3 @@ -1,34 +1,23 @@
     1.4 -Here I explore the design and capabilities of my system (called
     1.5 -=CORTEX=) which enables experiments in /embodied artificial
     1.6 -intelligence/ -- that is, AI which uses a physical simulation of
     1.7 -reality accompanied by a simulated body to solve problems.
     1.8 +Here I demonstrate the power of using embodied artificial intelligence
     1.9 +to attack the /action recognition/ problem, which is the challenge of
    1.10 +recognizing actions performed by a creature given limited data about
    1.11 +the creature's actions, such as a video recording. I solve this problem
    1.12 +in the case of a worm-like creature performing actions such as curling
    1.13 +and wiggling.
    1.14  
    1.15 -In the first half of the thesis I describe the construction of
    1.16 -=CORTEX= and the rationale behind my architecture choices. =CORTEX= is
    1.17 -a complete platform for embodied AI research. It provides multiple
    1.18 -senses for simulated creatures, including vision, touch,
    1.19 -proprioception, muscle tension, and hearing. Each of these senses
    1.20 -provides a wealth of parameters that are biologically
    1.21 -inspired. =CORTEX= is able to simulate any number of creatures and
    1.22 -senses, and provides facilities for easily modeling and creating new
    1.23 -creatures. As a research platform it is more complete than any other
    1.24 -system currently available.
    1.25 +To attack the action recognition problem, I developed a computational
    1.26 +model of empathy which allows me to use simple, embodied
    1.27 +representations of actions (which require rich sensory data), even
    1.28 +when that sensory data is not actually available. The missing sense
    1.29 +data is ``imagined'' by the system by combining previous experiences
    1.30 +gained from unsupervised free play.
    1.31  
    1.32 -In the second half of the thesis I develop a computational model of
    1.33 -empathy, using =CORTEX= as a base. Empathy in this context is the
    1.34 -ability to observe another creature and infer what sorts of sensations
    1.35 -that creature is feeling. My empathy algorithm involves multiple
    1.36 -phases. First is free-play, where the creature moves around and gains
    1.37 -sensory experience. From this experience I construct a representation
    1.38 -of the creature's sensory state space, which I call \phi-space. Using
    1.39 -\phi-space, I construct an efficient function for enriching the
    1.40 -limited data that comes from observing another creature with a full
    1.41 -compliment of imagined sensory data based on previous experience. I
    1.42 -can then use the imagined sensory data to recognize what the observed
    1.43 -creature is doing and feeling, using straightforward embodied action
    1.44 -predicates. This is all demonstrated with using a simple worm-like
    1.45 -creature, and recognizing worm-actions in video.
    1.46 -
    1.47 -
    1.48 -empathy is important 
    1.49 -cortex tests that idea
    1.50 \ No newline at end of file
    1.51 +In order to build this empathic, action-recognizing system, I created
    1.52 +a program called =CORTEX=, which is a complete platform for embodied
    1.53 +AI research. It provides multiple senses for simulated creatures,
    1.54 +including vision, touch, proprioception, muscle tension, and
    1.55 +hearing. Each of these senses provides a wealth of parameters that are
    1.56 +biologically inspired. =CORTEX= is able to simulate any number of
    1.57 +creatures and senses, and provides facilities for easily modeling and
    1.58 +creating new creatures. As a research platform it is more complete
    1.59 +than any other system currently available.