Mercurial > cortex

     1 Here I demonstrate the power of using embodied artificial intelligence

     2 to attack the /action recognition/ problem, which is the challenge of

     3 recognizing actions performed by a creature given limited data about

     4 the creature's actions, such as a video recording. I solve this

     5 problem in the case of a worm-like creature performing actions such as

     6 curling and wiggling.

     7 

     8 To attack the action recognition problem, I developed a computational

     9 model of empathy (=EMPATH=) which allows me to use simple, embodied

    10 representations of actions (which require rich sensory data), even

    11 when that sensory data is not actually available. The missing sense

    12 data is ``imagined'' by the system by combining previous experiences

    13 gained from unsupervised free play.

    14 

    15 In order to build this empathic, action-recognizing system, I created

    16 a program called =CORTEX=, which is a complete platform for embodied

    17 AI research. It provides multiple senses for simulated creatures,

    18 including vision, touch, proprioception, muscle tension, and

    19 hearing. Each of these senses provides a wealth of parameters that are

    20 biologically inspired. =CORTEX= is able to simulate any number of

    21 creatures and senses, and provides facilities for easily modeling and

    22 creating new creatures. As a research platform it is more complete

    23 than any other system currently available.
author	Robert McIntyre <rlm@mit.edu>
date	Sun, 23 Mar 2014 22:20:44 -0400
parents	853377051f1e
children	c20de2267d39