I have a rather unique problem, that I hope to work out a method that can be duplicated with some logic & rules to consistently achieve high results.
The problem / challenge.
1) There are 14 sliders - Each slider from 0 & 999.
2) Sliders are as follows;
- Downforce front
- Downforce rear
- Height front
- Height rear
- Anti Roll-bar front
- Anti roll-bar rear
- Tyre pressure front
- Tyre pressure rear
- Suspension front
- Suspension rear
- Brake size
- Brake balance
3) Each slider has an optimum value.
4) You get a description (Hint) at the start;
- Downforce 'High'
- Height 'Low'
- Caster 'Low'
- Anti Roll-bar 'High' Etc...
5) You get 6 attempts.
6) Each attempt you get suggestions (Hints) on random sliders of lower or higher. You get 1-4 suggestions per attempt.
7) There is an overall percent of accuracy (all sliders are optimum = 100%). Sliders are weighted differently, percent is not divided equally between all sliders.
8) Each attempt you get 'Better' 'No Change' or 'Worse'.
9) Percent turns into descriptive text once it reaches X percent (Good 85% - Very Good 88% - Excellent 91% - Near Perfect 95%).
Screenshot of problem here.
Screenshot of hints pre first attempt here.
My recent method was to start my attempts at the hints extreme Low 0 & High 999. Each move would be lower or higher 200 points. Would continue lowering & increasing by 200 points. I would adjust them depending on sliders & suggestions. It works to a point (around 80% & 88%) which isn't good enough. I need to fine tune the method & create rules so I can apply it to all other attempts. Maybe my method isn't good enough & mathematically speaking, terrible!
If anyone can put forward a method, theory with some logic & rules would be great. If any more information is required please let me know.
Thanks for reading,