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6.804-bayesianRL

Experimental Setup:

2 Groups of 5 Participants:

First Group:

We are going to have you play a game in which you seek to maximize your reward. The current state is presented in the
center with the movement options as the arrows around it. Your current total reward is on the top right, and your
current step count is on the top left. At any point when you gain or lose points, the reward of that step will be
presented above the state.

You will play four games, each for three phases.

Second Group:

We are going to have you play a game in which you seek to maximize your reward in 300 steps. The current state is
presented in the center with the movement options as the arrows around it. Your current total reward is on the top
right, and your current step count is on the top left. At any point when you gain or lose points, the reward of that
step will be presented above the state.

You will play four games, each for three phases.

Run the following command in the terminal for each game:

python [game] [filename]

Each participant will play each of the games below 3 times:

SlipperyChainGame.py
    
LoopGame.py
    
LoopDeadEndGame.py
    
LoopDiffTransGame.py

Make sure to input a filename to store the user's gameplay.

Note: Make sure that the participant does not see you starting the game, as the names will provode clues to the structure of the models.

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  • Python 100.0%