Combat
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| Combat | |
 | |
| Author(s) | MN |
| Extends | TeamRobot |
| Targeting | DC/GuessFactor SwarmTargeting RandomTargeting |
| Movement | DC/WaveSurfing DC/FlatMovement Anti-gravity DC/ShrapnelDodging |
| Released | 2011 |
| Current Version | 3.15.0 |
| Code Size | 26330 |
| Download | |
Background Information
- How competitive it is?
1v1 - #42 APS, #11 Survival, #10 PL
meleerumble - #9 APS, #6 Survival, #8 PL
teamrumble - #3 APS, #2 Survival, #3 PL
neoroborumble - #1 APS, #1 Survival, #1 PL
Strategy
- How does it move?
- Multi-mode
- Wave Surfing/Wall Smoothing
- Old Skool anti-gravity movement boosted with precise prediction/wall avoidance
- How does it fire?
- Guess factor targeting with dynamic clustering segmented data.
- Using dynamic clustering/kernel density to estimate hit rate and choose bullet power. Working well in melee/team thanks to swarm targeting, shooting power 3 bullets against tight packs of bots, and owning rammers :) . Working acceptably against intermediate/weak bots in 1v1, but it is a waste of energy against surfers :( .
- How does it dodge bullets?
- Old Skool shrapnel dodging.
- Wave Surfing/Curve flattening.
- Enemy virtual bullets generated with dynamic clustering segmented data in both modes.
- How does the melee strategy differ from one-on-one strategy?
- Anti-gravity in melee/team.
- Multi-mode in 1v1
- Wave Surfing at long range.
- Anti-gravity at close range (anti-ramming/dive protection).
- How does it select a target to attack/avoid in melee ?
- What does it save between rounds and matches?
- Between matches: Nothing.
- Between rounds: Wave data.
Additional Information
- Where did you get the name?
- From the Atari 2600 game Combat.
- Can I use your code?
- Not open-source.
- What's next for your robot?
- Cool algorithms
Energy management with dynamic clustering segmented data for hit rate estimation. Should be cool to watch.DONE- Bomb sheltering evaluation to erase enemy virtual bullets.
- Rating improvement
Go to surfing for 1v1.DONEAnti-surfer gun for 1v1.DONECurve flattening for 1v1.DONEPrecise prediction/max escape angle calculation.DONE- Classification tuning.
Fast math classes.DONE- Bullet Shadow evaluation.
- A k-d tree to optimize dynamic clustering.
- Minimum risk movement.
- Refining all the above
- What other robot(s) is it based on?
- Shadow (swarm targeting), DrussGT (energy management, DC classifiers, Simonton wall distance), Diamond (gaussian kernel function).
- Rednaxela´s FastTrig
