Difference between revisions of "ScalarR/Random thoughts"
< ScalarR
Jump to navigation
Jump to search
m (What makes wave surfing effective?) |
m (What makes wave surfing effective?) |
||
| Line 1: | Line 1: | ||
| + | This page is a collection of some random thoughts. Feel free to start a discussion. | ||
| + | |||
| + | |||
| + | === On making a top bot === | ||
| + | |||
; What really makes a bot strong overall? | ; What really makes a bot strong overall? | ||
: Excessive tuning of every single detail. See the logs in [[ScalarR/Version History|/Version History]]. | : Excessive tuning of every single detail. See the logs in [[ScalarR/Version History|/Version History]]. | ||
| Line 14: | Line 19: | ||
: Active bullet shielding may help against the top bots, but about general rumble, there's still much room in accurately predicting & controlling the opponents' targeting. Reducing b in a / (a + b) is more efficient once a is larger. | : Active bullet shielding may help against the top bots, but about general rumble, there's still much room in accurately predicting & controlling the opponents' targeting. Reducing b in a / (a + b) is more efficient once a is larger. | ||
| + | |||
| + | === On why things work === | ||
; What makes wave surfing effective? | ; What makes wave surfing effective? | ||
| − | : Wave surfing is effective because it actively find movement patterns that the opponent is hard to hit, and keep the current pattern as long as no more hits are made. This explains why adding even a little flattening to even some simple learners hurts performance a lot, so does adding any randomness. This disobeys the common belief that wave surfing does well by flattening the movement profile. Flattening the movement profiles | + | : Wave surfing is effective because it actively find movement patterns that the opponent is hard to hit, and keep the current pattern as long as no more hits are made. This explains why adding even a little flattening to even some simple learners hurts performance a lot, so does adding any randomness. This disobeys the common belief that wave surfing does well by flattening the movement profile. Flattening the movement profiles shown by the guns is how it scores, not how it actually works. |
Revision as of 16:44, 17 January 2023
This page is a collection of some random thoughts. Feel free to start a discussion.
On making a top bot
- What really makes a bot strong overall?
- Excessive tuning of every single detail. See the logs in /Version History.
- What affects performance the most?
- Targeting and movement are equally important. Strong targeting helps more against strong opponents, while strong movement earns more from the weak.
- How to make a top movement from scratch?
- First make it right. Then spend some time tuning bandwidth and distancing. Good aiming models can be used as good danger models, further tuning may not help much. Flatteners aren't necessary.
- How to make a top gun from scratch?
- Basic attributes + wall attributes + machine learning on whole rumble data = good to go. Fancy features may help against some bots, but may not help too much overall.
- What may be the next big innovation?
- Active bullet shielding may help against the top bots, but about general rumble, there's still much room in accurately predicting & controlling the opponents' targeting. Reducing b in a / (a + b) is more efficient once a is larger.
On why things work
- What makes wave surfing effective?
- Wave surfing is effective because it actively find movement patterns that the opponent is hard to hit, and keep the current pattern as long as no more hits are made. This explains why adding even a little flattening to even some simple learners hurts performance a lot, so does adding any randomness. This disobeys the common belief that wave surfing does well by flattening the movement profile. Flattening the movement profiles shown by the guns is how it scores, not how it actually works.
