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rlm@432
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1 Here I explore the design and capabilities of my system (called
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rlm@432
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2 =CORTEX=) which enables experiments in /embodied artificial
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rlm@432
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3 intelligence/ -- that is, AI which uses a physical simulation of
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4 reality accompanied by a simulated body to solve problems.
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rlm@432
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5
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rlm@432
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6 In the first half of the thesis I describe the construction of
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7 =CORTEX= and the rationale behind my architecture choices. =CORTEX= is
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rlm@432
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8 a complete platform for embodied AI research. It provides multiple
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9 senses for simulated creatures, including vision, touch,
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10 proprioception, muscle tension, and hearing. Each of these senses
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11 provides a wealth of parameters that are biologically
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12 inspired. =CORTEX= is able to simulate any number of creatures and
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13 senses, and provides facilities for easily modeling and creating new
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14 creatures. As a research platform it is more complete than any other
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15 system currently available.
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16
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17 In the second half of the thesis I develop a computational model of
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18 empathy, using =CORTEX= as a base. Empathy in this context is the
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19 ability to observe another creature and infer what sorts of sensations
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20 that creature is feeling. My empathy algorithm involves multiple
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21 phases. First is free-play, where the creature moves around and gains
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22 sensory experience. From this experience I construct a representation
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23 of the creature's sensory state space, which I call \phi-space. Using
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24 \phi-space, I construct an efficient function for enriching the
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25 limited data that comes from observing another creature with a full
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26 compliment of imagined sensory data based on previous experience. I
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27 can then use the imagined sensory data to recognize what the observed
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28 creature is doing and feeling, using straightforward embodied action
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29 predicates. This is all demonstrated with using a simple worm-like
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30 creature, recognizing worm-actions in video.
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31
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