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completeing first third of first chapter.
author Robert McIntyre <rlm@mit.edu>
date Mon, 24 Mar 2014 20:59:35 -0400
parents c1e6b7221b2f
children 8e52a2802821
comparison
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440:b01c070b03d4 441:c20de2267d39
4 the creature's actions, such as a video recording. I solve this 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 5 problem in the case of a worm-like creature performing actions such as
6 curling and wiggling. 6 curling and wiggling.
7 7
8 To attack the action recognition problem, I developed a computational 8 To attack the action recognition problem, I developed a computational
9 model of empathy (=EMPATH=) which allows me to use simple, embodied 9 model of empathy (=EMPATH=) which allows me to recognize actions using
10 representations of actions (which require rich sensory data), even 10 simple, embodied representations of actions (which require rich
11 when that sensory data is not actually available. The missing sense 11 sensory data), even when that sensory data is not actually
12 data is ``imagined'' by the system by combining previous experiences 12 available. The missing sense data is ``imagined'' by the system by
13 gained from unsupervised free play. 13 combining previous experiences gained from unsupervised free play.
14 14
15 In order to build this empathic, action-recognizing system, I created 15 In order to build this empathic, action-recognizing system, I created
16 a program called =CORTEX=, which is a complete platform for embodied 16 a program called =CORTEX=, which is a complete platform for embodied
17 AI research. It provides multiple senses for simulated creatures, 17 AI research. It provides multiple senses for simulated creatures,
18 including vision, touch, proprioception, muscle tension, and 18 including vision, touch, proprioception, muscle tension, and