runningScore = 0
state = track.reset()
runs = args.runs if args.train else 10
for run in range(runs):
" for every lap or run (when training) run it. "
score = 0
state = track.reset()
maxTrackScore = 1000
for _track in range(maxTrackScore):
" For every track out of the maximum score "
if args.train:
action, coefficient = actor.chooseActionTrain(state)
else:
action = actor.chooseAction(state)
newState, reward, done, die = track.step(action *
np.array([2., 1., 1.]) +
np.array([-1., 0., 0.]))
track.render()
if args.train and actor.storeInBuffer(
(state, action, coefficient, reward, newState)):
print('updating model file')
actor.update()
score += reward
state = newState
