RaceRoom Racing Experience: Difference between revisions

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*** Run multiple races with the same car class
*** Run multiple races with the same car class
*** But, if you're in a new car class or at a new track, it will use average laptimes for the car class or track you've raced before
*** But, if you're in a new car class or at a new track, it will use average laptimes for the car class or track you've raced before
*** Worst case scenario you're at a new car/track combo and there's no average laptimes. It's not clear what happens in this case but it's likely it completely breaks as it has no car or track to grab laptimes from to adjust Adaptive AI.
*** Worst case scenario you're at a new car/track combo and there's no average laptimes for either car or track...
**** Based on an experiment, it might be judging AI level based on existing average laptimes from other car/track combos
**** <strike>It's not clear what happens in this case but it's likely it completely breaks as it has no car or track to grab laptimes from to adjust Adaptive AI.</strike>
* '''Quotes'''
* '''Quotes'''
** From [https://forum.kw-studios.com/index.php?threads/adaptive-ai.14262/#post-194050 this post]
** From [https://forum.kw-studios.com/index.php?threads/adaptive-ai.14262/#post-194050 this post]
Line 32: Line 34:
*** "If the AI can't find info on that particular track, it'll take the average of all the tracks you've done with that particular car-class. And vice-versa for new cars on a track you've already run with a different class."
*** "If the AI can't find info on that particular track, it'll take the average of all the tracks you've done with that particular car-class. And vice-versa for new cars on a track you've already run with a different class."
*** "The more tracks you've done, the bigger the chance the adaptive AI will hit the right spot in the first try. Which is where the 4-5 tracks needed come in."
*** "The more tracks you've done, the bigger the chance the adaptive AI will hit the right spot in the first try. Which is where the 4-5 tracks needed come in."
=== Adaptive AI Scratchpad ===
<pre><nowiki>
===
240703
R3E Adaptive AI Tracks Run with DTM 2023 Cars and 20 AI 240703:
- No qualifying always grids you 6th. I wonder if that means the goal of AAI is to always give you a chance at a win.
1. Donington
2. Mid Ohio
3. Imola
4. Brands Hatch Grand Prix
5. Brno
6. Zandvoort
7. Zolder
8. Hockenheimring
  ^ From being destroyed to comfortably running 10th mid pack, kind of odd
  ^ Maybe there's a minimum laps recorded count before AAI kicks in
  ^ Noticed AI were less aggressive with punting from behind and passed with more care
  ^ Noticing rubberbanding. They never seem to get more than 3-5sec away and you only really catch up if there's an accident.
9. Hungaroring
  ^ 17th
  ^ AI continue to be less aggressive and pass with more pass
  ^ Similar rubberbanding
10. Interlagos
  ^ 18th. Was last for a while until the AI made some mistakes.
  ^ Similar rubberbanding
11. Monza
  ^ 1st, comfortable 5-3 for a while, worked my way up late, held 1st +0.7sec, almost gave it up
  ^ Forgot to switch car. Hope that didn't mess things up.
12. Moscow
  ^ 1st, Comfortably top 3
  ^ New track to me, nice track though
  ^ There's some weird quirk with isiMotor AI where once you get them to a competitive AI level they seem to run into you less and become more situationally aware of you
 
Conclusions:
- It takes more races/laps than you think while doing it but it's not a crazy amount either
- R3E is underrated. Racing with AI is very decent once dialed in.
  ^ Unpopular but fun cars and tracks are a cool feature of R3E
 
Experiment: Untrained cars at trained track 240703
- Praga R1 (Untrained) at Moscow (Trained)
- Expectations:
  - > If working as expected (ie. has track data), comfortably top 5
  - If working but not as expected, mid pack 10-20th
  - If not working at all, solid last place
- Results:
  - 5th, comfortably top 5, but AI hot on my tail
  - Maybe some rubberbanding
  - New car, needed to practice to get up to speed
 
Experiment: Untrained cars at untrained track 240703
- WTCR 2022 Honda Civic TCR (Untrained) at Red Bull Ring (Untrained)
- Expectations:
  - If working as expected (ie. no car or track data), solid last place
  - > If working but not as expected (maybe using random track data), top to mid pack
  - If not working at all, solid last place
- Results:
  - 4th, comfortably top 5, rough start and fell to 8th but climbed back up in a few laps
  - Interesting it was apparently able to judge AI level based on average laptimes from other car/tracks because it couldn't have known my laptimes until I raced this car+track combo.
  - New car, needed to practice to get up to speed
 
Next Steps:
- Now that DTM 2023 are trained, how well will AAI apply it to other car sets on the trained tracks?
- Consider the gridding 6th (when no qualifying) for GTR2 AI tweaks
===
</nowiki></pre>

Revision as of 05:40, 4 July 2024

Force Feedback

  • Really quite impressive these days. Might be better than rFactor 1, original Assetto Corsa, and different but comparable in quality to Assetto Corsa Competizione. -Shovas, SimuCube 2 Pro

Adaptive AI

  • Overview
    • Adaptive AI adjusts the AI difficulty level for the current car/track combo by comparing the player's average lap over the last 10 laps against AI grid's average fastest lap
  • Tips
    • Quickly Training the Adaptive AI:
      • Run a number of short 10min races to quickly train the AI
      • Skip practice and qualifying if you already know the track to get through it more quickly
      • Skipping qualifying should be fine as Adaptive AI only trains on Race session lap times
  • Tools
    • The Adaptive AI Primer tool can be used to 'seed' the laptimes data used by Adaptive AI which may help speed up the process of adapting
  • Caveats
    • How Adaptive AI was designed to be trained:
      • Run multiple races at the same track
      • Run multiple races with the same car class
      • But, if you're in a new car class or at a new track, it will use average laptimes for the car class or track you've raced before
      • Worst case scenario you're at a new car/track combo and there's no average laptimes for either car or track...
        • Based on an experiment, it might be judging AI level based on existing average laptimes from other car/track combos
        • It's not clear what happens in this case but it's likely it completely breaks as it has no car or track to grab laptimes from to adjust Adaptive AI.
  • Quotes
    • From this post
      • "The AAI works by comparing the average fastest lap of the AI grid to the players average lap over the last 10 laps."
      • "So you need to run enough laps for the grid to get spaced out a bit. otherwise they're being held up either by the player or other AI."
      • "4-5 laps is usually enough to get a decent lap-time for the AI."
      • "The player has to run at race-pace during this as well, otherwise the player average will plummet and the whole thing will be for naught."
      • "It will take a few attempts before the AI starts getting up to speed. So do one track/car combo repeatedly until it's up to speed."
      • "Then switch to the next. Rinse and repeat until you have 4-5 tracks done with that class, and by then the law of averages should mean any new track will start in roughly the right place."
      • "Yes, [Adaptive AI] only trains during race-sessions. And yes, you do have to have AI on-track for it to work."
      • "If the AI can't find info on that particular track, it'll take the average of all the tracks you've done with that particular car-class. And vice-versa for new cars on a track you've already run with a different class."
      • "The more tracks you've done, the bigger the chance the adaptive AI will hit the right spot in the first try. Which is where the 4-5 tracks needed come in."

Adaptive AI Scratchpad

===
240703

R3E Adaptive AI Tracks Run with DTM 2023 Cars and 20 AI 240703:
- No qualifying always grids you 6th. I wonder if that means the goal of AAI is to always give you a chance at a win.
 1. Donington
 2. Mid Ohio
 3. Imola
 4. Brands Hatch Grand Prix
 5. Brno
 6. Zandvoort
 7. Zolder
 8. Hockenheimring
  ^ From being destroyed to comfortably running 10th mid pack, kind of odd
  ^ Maybe there's a minimum laps recorded count before AAI kicks in
  ^ Noticed AI were less aggressive with punting from behind and passed with more care
  ^ Noticing rubberbanding. They never seem to get more than 3-5sec away and you only really catch up if there's an accident.
 9. Hungaroring
  ^ 17th
  ^ AI continue to be less aggressive and pass with more pass
  ^ Similar rubberbanding
10. Interlagos
  ^ 18th. Was last for a while until the AI made some mistakes.
  ^ Similar rubberbanding
11. Monza
  ^ 1st, comfortable 5-3 for a while, worked my way up late, held 1st +0.7sec, almost gave it up
  ^ Forgot to switch car. Hope that didn't mess things up.
12. Moscow
  ^ 1st, Comfortably top 3
  ^ New track to me, nice track though
  ^ There's some weird quirk with isiMotor AI where once you get them to a competitive AI level they seem to run into you less and become more situationally aware of you
  
Conclusions:
- It takes more races/laps than you think while doing it but it's not a crazy amount either
- R3E is underrated. Racing with AI is very decent once dialed in.
  ^ Unpopular but fun cars and tracks are a cool feature of R3E
  
Experiment: Untrained cars at trained track 240703
- Praga R1 (Untrained) at Moscow (Trained)
- Expectations:
  - > If working as expected (ie. has track data), comfortably top 5
  - If working but not as expected, mid pack 10-20th
  - If not working at all, solid last place
- Results: 
  - 5th, comfortably top 5, but AI hot on my tail
  - Maybe some rubberbanding
  - New car, needed to practice to get up to speed
  
Experiment: Untrained cars at untrained track 240703
- WTCR 2022 Honda Civic TCR (Untrained) at Red Bull Ring (Untrained)
- Expectations:
  - If working as expected (ie. no car or track data), solid last place
  - > If working but not as expected (maybe using random track data), top to mid pack
  - If not working at all, solid last place
- Results:
  - 4th, comfortably top 5, rough start and fell to 8th but climbed back up in a few laps
  - Interesting it was apparently able to judge AI level based on average laptimes from other car/tracks because it couldn't have known my laptimes until I raced this car+track combo.
  - New car, needed to practice to get up to speed
  
Next Steps:
- Now that DTM 2023 are trained, how well will AAI apply it to other car sets on the trained tracks?
- Consider the gridding 6th (when no qualifying) for GTR2 AI tweaks
===