Human Cognitive Emulation

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Human Cognitive Emulation

• By Lee Rumpf

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Abstract
This project attempts to accurately model human
responses to stimuli. Using a survey format, this
research hopes to produce a unique response to a
stimuli based on information gained about the
user. Analyzed solely on its own, the
ramification of this project can perhaps draw
broad conclusions about groups of people and how
they respond. When combined with other techniques
of emulating human though patterns, computer
programs can come closer to representing
accurately human responses.
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Scope of Project/Expected Results

• Users placed into like groups
• Closest match with group will predict response
• Smaller groups more accurate results

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Similar Projects

• Sandia National Labs is doing a much more complex
  version of this project with many different
  approaches adding up to a complete psychological
  profile.
• Dr. Ann Speed is one of the lead psychologists at
  Sandia working on Cognitive Emulation.

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Approach

• Python
• text-based
• evolutionary programming

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Construction
def main() answers open('answers.txt',
'r') array array
answers.read().split("\n") prompt
raw_input("new or name ") if prompt
"new" prompt raw_input("name
") outfile open(prompt, 'w')
outfile.write(prompt"\n")
else outfile open(prompt,
'w') outfile.write(prompt"\n")
test "france","balls","home","salad","poo
dle","oar","classic rock","mary","door","math"
count 0 hard dict(zip(test,
Nonelen(test))) for a in test
count count 1 for k
in range(len(array)-1)
temp arrayk.split(',')
ans tempcount
hardak ans answers.close()
The program is written in Python and as of now
designed to survey the user for a response to the
stimuli.
Current work includes creating a visual output to
both represent and quantify results.
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Future outputs
Group
Individual

• France
• Balls
• Home
• Salad
• Poodle
• Oar
• Classic Rock
• Mary
• Door
• Math

• France
• Balls
• Home
• Salad
• Poodle
• Oar
• Classic Rock
• Mary
• Door
• Math

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• ROCK ON