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Ok this is my first try in machine learning, this is DQN for Pong!
I want to add my own flavor by adding pressure touch to paddle movements, such that the harder I press in a direction it moves faster to a max speed.
Does it makes sense if I apply the floating point outputs of sigmoid directly to speed control? Or should I make multiple outputs to represent different "steps" of pressure/speed?
question
machine learning
dqn
game
pong
reinforced learning
ai