They have 350 hrs of playing per level. They could brute force on these parameters.
1. Detect to_avoid moving obstacles
2. Detect to_avoid stationary obstacles (gaps)
3. Player moves (jump (left, right)(up, far, farthest), walk)
4. Success (hitting the flag, reaching princess)
Once above information is available on the screen, it becomes easily bruteforcible. I was hoping use of genetic algorithms i.e. they could have taken success from one part (path) of level and crossed it with another and tried that with across levels. But there won't be a generic strategy or learning anyways as there's fair bit of randomness. So this does seem like brute forcing for success path
1. Detect to_avoid moving obstacles
2. Detect to_avoid stationary obstacles (gaps)
3. Player moves (jump (left, right)(up, far, farthest), walk)
4. Success (hitting the flag, reaching princess)
Once above information is available on the screen, it becomes easily bruteforcible. I was hoping use of genetic algorithms i.e. they could have taken success from one part (path) of level and crossed it with another and tried that with across levels. But there won't be a generic strategy or learning anyways as there's fair bit of randomness. So this does seem like brute forcing for success path