Comparing Results Between Shielders

Shielding Robot	APS	Survival	Pairs Won	Specialization	Notes
jk.precise.EnergyDome 1.1	56.24	63.19	58.6%	20,957
jk.precise.EnergyDome 1.5	58.78	65.73	61.3%	24,095
rsim.micro.uCatcher 0.1	30.65	41.41	27.8%	8,620
rsim.mini.BulletCatcher 0.4	67.02	78.06	82.5%	4,043	(1)
xander.cat.Spitfire 1.0	32.31	43.41	33.3%	18,109	(2)
xander.cat.Spitfire 1.1	40.08	50.16	42.3%	22,313
wiki.BasicBulletShielder 1.0	19.08	28.11	14.7%	7,419

Notes:

1. Has light-weight second mode that takes over when shielding fails or when opponent is low energy.
2. A bit handicapped by slow firing response. Only fires first when opponent disabled and no active waves in play.

Whoops! Thanks Chase. I didn't realize BasicBulletShielder was in the rumble already.

No problem. The one I made is definitely the bottom of the pack. But I had only decided to make a very simple to show how its done to others. It only fires when the enemy is disabled.

The only way I think I can improve it thought, is to profile what kind of shot the enemy is firing and adjusting to it.

Yup, EnergyDome uses a VG to match which type of HOT/GF0 calculation they are doing, and also keeps an offset tally in case they consistently shoot slightly to the side. I've actually considered going all out and using a Kd-Tree to try to predict how much offset they will shoot with, but I'm a bit scared as to what the results might be :-p

It also doesn't run away under any circumstances, and is very careful to stay at GF0 for the ramming kill.

When I first experimented with Bullet Shielding, what I was trying to achieve was a rammer which closed in using shielding and 0.1 powered bullets, and switched to power 3 bullets at point blank range.

Attack with movement and defend with targeting. The opposite of the Wave Surfing/GuessFactor combination.

But it was so hard to predict where incoming bullets were heading I gave up. Until you showed that competitive Bullet Shielding is possible.

The trick is to give them a really easy target that makes their targeting predictable. Ramming has a big spike somewhere around GF0, but if they start moving laterally and you follow them you aren't at exactly GF0 any more for the waves that hit you, so who knows where they will shoot.

If the opponent uses only real waves, then you can try to plot a course where waves always hit at GF0.

If virtual waves are used, it gets trickier. You have to guess with which bullet power virtual waves are being fired. That could be estimated by analysing onHitByBullet and onBulletHitBullet events.

If other targeting strategy, like pattern matching, is being used, then it could also be estimated with onHitByBullet and onBulletHitBullet events.

If multiple bullet powers are used at the same time, then staying still seems a better alternative than ramming, as all deterministic strategies converge to head-on targeting. Who would guess SittingDuck movement is a viable strategy?

Surpass MaxRisk.

And then, maybe squeeze the code into the smallest codesize class as possible.

I doubt you would be able to get any smaller than a minibot. But it sounds like it could be very successful. Good luck.