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Caroline and I are studying how we computational assess and act on risk!

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9.66-FInal-Project-

Using Bayesian models to approxiamte risk in BART tasks

Set up

Python 3.5 with Pygame

pip install pygame

Experiment 1 - Loss Aversion

python3 game.py --name="NAME" --gender="N" --age="0" --balloons=10 --course=0 --exp=1 --lossAversion=True
python3 game.py --name="NAME" --gender="N" --age="0" --balloons=10 --course=0 --exp=1 --lossAversion=False

Experiment 2 - Standardize Distribution for Risk Measurement

python3 game.py --name="NAME" --gender="N" --age="0" --balloons=10 --course=0 --exp=2 --lossAversion=True --dist="GAUSSIAN 10 4 2" --obs="1,5,5,4,1,6,7,5,4,7"

Experiment 3 - Hypothesis Space

python3 game.py --name="NAME" --gender="N" --age="0" --balloons=10 --course=0 --exp=2 --lossAversion=True --seenGraphs=True

python3 game.py --name="NAME" --gender="N" --age="0" --balloons=10 --course=0 --exp=2 --lossAversion=True --seenGraphs=False

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Caroline and I are studying how we computational assess and act on risk!

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