baseline q model.py

num_actions = 3  # [move_left, stay, move_right]
hidden_size = 100 # Size of the hidden layers
grid_size = 10 # Size of the playing field

def baseline_model(grid_size,num_actions,hidden_size):
    #seting up the model with keras
    model = Sequential()
    model.add(Dense(hidden_size, input_shape=(grid_size**2,), activation='relu'))
    model.add(Dense(hidden_size, activation='relu'))
    model.add(Dense(num_actions))
    model.compile(sgd(lr=.1), "mse")
    return model