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In contrast, here's what is effectively an oracle machine playing mario kart: https://www.youtube.com/watch?v=ZBNgbJ5hXtQ (Amazingly detailed) info: http://tasvideos.org/5243S.html
In contrast, here's what is effectively an oracle machine playing mario kart: https://www.youtube.com/watch?v=ZBNgbJ5hXtQ (Amazingly detailed) info: http://tasvideos.org/5243S.html
Pretty interesting I must say. Have to admit though, I kind of expected the self driving AI to be trying to win Grand Prix or Versus races instead of doing well in Time Trials. But hey, I can see how that would be utterly painful to try and set up, especially given how times you get hit by items or rammed off the track in more recent games.
Step 2 is to make AI figure out how to return to the ideal path through the course when other people are stealing your items or shelling you.
step 3 is to make the AI figure out how to counter attack to slow down the opponents.
Step 4 is OH GOD WE TAUGHT THE AI HOW TO ATTACK RUN FOR YOUR LIVES.
So the author did a proper test of the model by scoring it on an unseen track to make sure it generalizes! This is very awesome!
Congrats on finishing the project! As you've already linked at the bottom of your post, it's possible that OpenAI could've solved most of your I/O issues. One thing I'd suggest is exploring a reward function, instead of using only pre-recorded training data. That is, give the AI a goal to complete (in this case, finish the race) and let it learn by itself!
EDIT: to clarify: what should I google for?
Congrats on finishing the project! As you've already linked at the bottom of your post, it's possible that OpenAI could've solved most of your I/O issues. One thing I'd suggest is exploring a reward function, instead of using only pre-recorded training data. That is, give the AI a goal to complete (in this case, finish the race) and let it learn by itself!
I would love to learn how to do that - any suggestions? EDIT: to clarify: what should I google for?
Congrats on finishing the project! As you've already linked at the bottom of your post, it's possible that OpenAI could've solved most of your I/O issues. One thing I'd suggest is exploring a reward function, instead of using only pre-recorded training data. That is, give the AI a goal to complete (in this case, finish the race) and let it learn by itself!
I would love to learn how to do that - any suggestions? EDIT: to clarify: what should I google for?
https://github.com/openai/universe-starter-agent
OpenAI's example universe agent. Remember that while their goal is an agent that works in any and all environments (read: games), you could certainly optimize yours just for MarioKart.
Quote: "Driving a new (untrained) section of the Royal Raceway:" So the author did a proper test of the model by scoring it on an unseen track to make sure it generalizes! This is very awesome!
Next, have it upload its race results to kartlytics