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A game to aid research on video games' relationship to reaction times in the context of reinforcement learning

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Sit, Boy!

Running the Game Without SQL Backend

In main.py, comment out every line referencing the sqlEventHandler object.

To run the game, you will need to install pygame: https://www.pygame.org/wiki/GettingStarted

python3 -m main.py

Planning Sheet

Game Dev Plan

  • needs backend. python to mysql backend.
    • testdb in mysql server community version localhost server (for now)
  • start menu with name of game and play or quit button
  • tutorial explaining what the game's about?
  • the game:
    • a dog is standing there, hanging out.
    • you tell the dog to sit
    • the dog sits after a random time
    • you press the 'reward' button
      • time it takes between sit and reward is recorded and sent to db
    • at end of game, show their score

elements of the program

3 parts to every game:

  1. window
  2. game loop
  3. event handler

the big parts of this game:

  1. sprite animations
    • stand, lick, sit, walk, run
  2. random time pass
    • a random double value translated to seconds - 1-5 seconds
  3. menu
  4. user interactions
    • click buttons
    • command sit
    • give reward

organizing the code

  • sprite sheet
  • sprite animation
  • main
    • event handler
    • game loop
    • window

features left to implement

  • dynamic window for different user screens
    • mobile
    • desktop
    • tablet
  • db connection
    • animation update insert event
    • user input update insert event
    • demographics data collection
  • user reward system
    • basic instructions in the game loop: when the dog sits down completely, press the enter/return key to reward them.
  • game instructions page
    • potential instruction locations:
      • on start menu
      • behind a menu button to access instructions
      • behind a game button to access instructions (pauses game while this happens)

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A game to aid research on video games' relationship to reaction times in the context of reinforcement learning

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