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 recognize actions using

    10 simple, embodied representations of actions (which require rich

    11 sensory data), even when that sensory data is not actually

    12 available. The missing sense data is ``imagined'' by the system by

    13 combining previous experiences 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	Mon, 24 Mar 2014 20:59:35 -0400
parents	c1e6b7221b2f
children	8e52a2802821