XanderCat

XanderCat
Author(s)	Skotty
Extends	AdvancedRobot
Targeting	GF / Linear / Anti-Mirror
Movement	WS(GoTo) / Anti-Mirror / RamEscape / IdealPosition
Released	2011-5-20 (v 1.0)
Best Rating	#20 (v 9.15)
Current Version	9.15
Code License	GCWCD
Download

Introduction

MegaBot based on my "Xander" robot framework with pluggable guns, radars, and drives. XanderCat is the flagship of my robot fleet. It is a multi-mode robot using multiple guns and drives. It's main gun is a guess factor gun, and the main drive is a wave surfing drive (GoTo-style), but a number of other guns and drives exist for special situations. Both the main gun and drive are currently using a hybrid form of dynamic clustering. The drive is somewhat unique in that it decides where it wants to go and goes there directly (no orbiting -- though the path still is somewhat orbital in nature due to distancing -- and no wall stick while driving).

Best against: Generally a good performer; probably most notable for having effective anti-mirroring capabilities.

Worst against: DrussGT of course.

Arch Nemisis: lazarecki.mega.PinkerStinker 0.7 (not only because I have trouble beating that one, but because I hate it's name)

Past Version Notes: For information on versions prior to the current series, see the XanderCat/History page.

Component Chain:

Default --> Basic Radar
  |
  v
RamScenario --> Ram Escape Drive, Linear Gun
  |
  v
MirrorScenario --> Anti-Mirror Drive, Anti-Mirror Gun
  |
  v
NoBulletWavesScenario --> Ideal Position Drive
  |
  v
Defaults --> Guess Factor Gun Array, Drive Array
                     |            ______|_______________
                     |           /                      \
                     |  Targeting Detector Drive   Direct Wave Surfing Drive
           __________|________________________
          /              \                    \
   Original Gun   Middle-Ground Gun   The Anti-Scarlet Gun

Name Origin?

Xander comes from my son's name Alexander. Cat was originally meant to be of the feline variety, as I like cats, have used the term in other software projects, and seemed appropriate. Cat could also be associated with the tractor variety, which I think also works (a tractor with a gun), and I'm fine if people make that association too.

Hybrid Dynamic Clustering?

XanderCat uses Dynamic Clustering (DC) in the sense that data about past waves is stored in a tree structure. For each wave, past data is pulled from the tree that as closely as possible matches the current situation, and that data is used to decide where to aim or drive. However, once the data is pulled, how to use it differs from classic DC. In classic DC, some form of kernel density algorithm is used to determine what to do. In the XanderCat hybrid approach, it behaves more like VCS, in that the data is logged into a factor array, and that array is surfed in the GoTo style.

Surfing Multiple Waves?

Starting with version 9.5, XanderCat now surfs up to 2 waves at a time. The general approach is as follows:

1. Calculate the first n best factor angles to drive to for the next wave to hit, each of which must be separated by a given amount. Each has an associated danger value.
2. From the end points of the n factor angles, continue to predict into the future surfing of the second wave to hit. For the second wave, only the best factor angle is used.
3. Add the first wave danger value to the corresponding second wave danger value for both the factor angles of the first wave. Choose which first wave factor angle to drive to by which has the lowest combined danger value.

Note the image below, where:

• a = reachable factor range for first wave
• b = minimum distance that must exist between first and second choice
• c = first choice for surfing first wave
• d = second choice for suring first wave
• e = current robot position

If the sum of the danger values represented by orange lines was less than the sum of the danger values represented by the red lines, the second choice for the first wave would be used.

Targeting Detector Drive?

This drive is a variation on my direct wave surfing drive, but instead of using previous hit data to build a factor array, it uses a combination of targeting detectors that are designed to detect specific types of targeting. Each targeting detector can add a data point to the factor array, with the data point weight based on how often the detector thinks it is detecting it's specific form of targeting. This system is designed to improve scores against robots that use predictable targeting (non-guess-factor), something I have had trouble getting my main wave surfing approach to handle as well as other top robots.

Linear Gun?

Originally I had both a Linear Targeting Gun and a Circular Targeting Gun in a gun array along with my Guess Factor Gun, but my Guess Factor Gun is now good enough that it works just as well by itself, so I removed the gun array (more recent versions have a gun array again, but all guns are variations on guess factor guns). However, the Linear Gun still makes an appearance against ramming robots. I hate to remove the Linear and Circular guns entirely, as I spent a lot of time on them when I first started Robocode.

Version Notes

Version Ranks

Note: Best Change and Worst Change are the change from previous version against the given opponent.

Note: Starting from version 6.4 onward in the table, I am ignoring nat.BlackHole 2.0gamma and nat.Samekh 0.4, as scores against them always fluctuate rather wildly.

Version	1-on-1 Rank	Top	Best Change	% Score Change	Worst Change	% Score Change
1.0	~475 / 805	59%	N/A	N/A	N/A	N/A
2.0	386 / 806	48%	mld.Wisdom 1.0	4.18 -> 76.13	SuperSample.SuperCrazy 1.0	61.97 -> 37.00
2.1	320 / 805	40%	dz.MostlyHarmlessNano 2.1	20.90 -> 63.01	jf.Dodger 1.1	78.98 -> 41.10
3.0	148 / 805	18%	gg.Wolverine 2.0	41.08 -> 94.57	xiongan.Xiongan 1.1	100.0 -> 74.39
3.1	145 / 804	18%	zyx.nano.RedBull 1.0	53.4 -> 85.3	pulsar.PulsarNano 0.2.4	89.3 -> 64.2
3.2	116 / 806	14%	ags.polished.PolishedRuby 1	28.5 -> 83.5	rsim.micro.uCatcher 0.1	91.7 -> 31.8
3.3	115 / 806	14%	nat.Samekh 0.4	24.9 -> 64.9	simonton.micro.GFMicro 1.0	62.2 -> 39.2
3.4	85 / 806	11%	dsx724.VSAB_EP3a 1.0	67.2 -> 93.4	intruder.PrairieWolf 2.61	65.6 -> 48.4
3.5.1	94 / 805	12%	rsim.micro.uCatcher 0.1	21.3 -> 96.4	nat.BlackHole 2.0gamma	69.2 -> 42.5
3.8	81 / 805	10%	synapse.rsim.GeomancyBS 0.11	36.5 -> 49.8	mn.Combat 1.0	80.1 -> 60.8
3.9	75 / 805	9.3%	pez.mini.ChironexFleckeri 0.5	42.2 -> 64.9	rsim.mini.BulletCatcher 0.4	57.7 -> 7.0
4.0	92 / 805	11%	rsim.mini.BulletCatcher 0.4	7.0 -> 72.1	nat.Samekh 0.4	73.3 -> 45.2
4.1	74 / 805 (73.66 APS)	9.2%	nat.Samekh 0.4	45.2 -> 75.7	staticline.whiskey.Whiskey 0.6	75.5 -> 57.5
4.2	74 / 805 (73.73 APS)	9.2%	mladjo.iRobot 0.3	53.8 -> 69.9	jcs.AutoBot 4.2.1	60.1 -> 35.1
4.3	74 / 805 (73.92 APS)	9.2%	kc.mini.Vyper 0.311	33.0 -> 53.0	positive.Portia 1.26e	60.0 -> 36.2
4.4	71 / 805 (74.11 APS)	8.8%	pez.frankie.Frankie 0.9.6.1	45.9 -> 62.8	fromHell.CHCI3 0.1.4	74.4 -> 55.7
4.4.1	71 / 805 (74.11 APS)	8.8%	brainfade.Fallen 0.63	45.7 -> 65.5	jam.micro.RaikoMicro 1.44	64.0 -> 49.8
4.5.1	71 / 805 (74.25 APS)	8.8%	spinnercat.CopyKat 1.2.3	51.6 -> 69.3	synapse.rsim.GeomancyBS 0.11	54.4 -> 38.6
4.6	71 / 805 (74.35 APS)	8.8%	deo.virtual.RainbowBot 1.0	54.8 -> 69.1	jab.DiamondStealer 5	80.6 -> 61.7
4.8	57 / 803 (76.46 APS)	7.1%	ar.QuantumChromodynamics 1.2.1	69.2 -> 90.5	nat.BlackHole 2.0gamma	60.8 -> 42.0
5.0	70 / 805 (74.37 APS)	8.7%	deo.FlowerBot 1.0	53.4 -> 84.6	kcn.unnamed.Unnamed 1.21	79.1 -> 58.0
5.1	49 / 815 (78.59 APS)	6.0%	ary.SMG 1.01	35.5 -> 90.3	nat.BlackHole 2.0gamma	54.4 -> 33.0
5.1.1	49 / 815 (78.75 APS)	6.0%	rz.Apollon 0.23	69.6 -> 94.0	nat.Samekh 0.4	72.7 -> 53.6
6.1.8	59 / 806 (76.65 APS)	7.3%	cx.Princess 1.0	47.8 -> 65.1	toz.Gnome 1.1	88.4 -> 61.6
6.2	59 / 806 (76.84 APS)	7.3%	nat.BlackHole 2.0gamma	42.1 -> 67.0	stelo.RamTrackSurfer 1.2	89.2 -> 72.9
6.3	56 / 806 (77.04 APS)	6.9%	kid.Gladiator .7.2	47.7 -> 65.5	nat.BlackHole 2.0gamma	53.4 -> 33.3
6.4	51 / 806 (78.22 APS)	6.3%	dmp.micro.Aurora 1.41	62.1 -> 79.1	myl.micro.NekoNinja 1.30	77.3 -> 61.3
6.5	48 / 808 (78.70 APS)	5.9%	ncj.MoxieBot 1.0	76.9 -> 92.6	bayen.nut.Squirrel 1.621	89.3 -> 74.9
6.7	45 / 807 (79.17 APS)	5.6%	apv.ScruchiPu 1.0	57.9 -> 79.5	trab.nano.AinippeNano 1.3	91.4 -> 74.7
6.8	42 / 808 (79.69 APS)	5.2%	trab.nano.AinippeNano 1.3	72.2 -> 89.5	rampancy.Durandal 2.2d	81.5 -> 69.4
9.0	46 / 827 (79.73 APS)	5.6%	N/A	N/A	N/A	N/A
9.0.1	45 / 827 (80.03 APS)	5.4%	ary.SMG 1.01	50.5 -> 76.4	ncj.MoxieBot 1.0	95.5 -> 75.5
9.1	43 / 828 (80.25 APS)	5.2%	kc.mini.Vyper 0.311	54.7 -> 60.7	ab.DangerousRoBatra 1.3	74.0 -> 66.7
9.2	38 / 828 (80.84 APS)	4.6%	Bemo.Sweet30 1.6.1	57.9 -> 68.3	kenran.mega.Pantheist	75.3 -> 57.1
9.3	34 / 829 (81.35 APS)	4.1%	ags.micro.Carpet 1.1	76.3 -> 89.2	ary.SMG 1.01	81.2 -> 64.9
9.4	33 / 830 (81.55 APS)	4.0%	kenran.mega.Panthiest	73.9 -> 85.3	bayen.nut.Squirrel 1.621	88.8 -> 80.9
9.5	30 / 830 (81.71 APS)	3.6%	wiki.BasicGFSurfer	65.3 -> 75.5	rampancy.Durandal 2.2d	80.3 -> 67.6
9.6	28 / 830 (81.91 APS)	3.4%	darkcanuck.Gaff 1.50	43.3 -> 52.4	kenran.mega.Panthiest 1.1	89.6 -> 78.9
9.7.1	25 / 832 (82.05 APS)	3.0%	rampancy.Durandal 2.2d	77.8 -> 88.3	brainfade.Fallen 0.63	64.0 -> 57.0
9.8	25 / 832 (82.12 APS, 1600 PL)	3.0%	asm.Statistas 0.1	70.4 -> 77.1	wcsv.PowerHouse.PowerHouse 1.7e3	53.9 -> 46.8
9.9.5	24 / 831 (82.37 APS, 1604 PL)	2.9%	ncj.MoxieBot 1.0	74.9 -> 86.0	cx.mini.Cigaret 1.31	64.9 -> 55.2
9.15	20 / 833 (82.74 APS, 1646 PL)	2.4%	janm.Jammy 1.0	75.2 -> 91.4	davidalves.net.DuelistMicro 1.22	72.1 -> 63.8

Version CPU Usage

All values are averages in milliseconds with the exception of those listed as Peak values, which are the maximum time in milliseconds encountered during a typical 35 round battle.

Version	Notes	Gun Avg/Tick	Gun Peak	Drive Avg/Tick	Drive Peak
6.5	Single wave surfing, single guess factor gun.	1.01	13.41, 8.77, 8.41, 7.15, 6.94	0.21	7.70, 7.61, 6.93, 6.93, 6.49
9.13	Multi-wave surfing, single guess factor gun.	0.301	6.23, 6.21, 5.82, 5.13, 4.74	0.775	22.52, 20.01, 16.26, 16.23, 15.94
9.14 / 10.0	Multi-wave surfing, gun array with 3 guess factor guns, Levy's KD Tree.	0.182	6.13, 6.07, 5.24, 4.05, 3.93	0.544	15.24, 14.55, 14.13, 13.91, 13.78

Series 1.x

This series of robots was released while work on the Xander framework was still ongoing. Targeting and drive strategies were somewhat simple. No surfing or guess-factor targeting.

Series 2.x

This series introduced my earlist concept on guess factor targeting. Drive strategy was still simple.

Series 3.x

This series introduced wave surfing, and improvements to the guess factor gun. Version 3.0 used a modified version of the BasicGTSurfer wave surfing drive as a reference point, with all later versions in the line using a wave surfing drive of my own design. Towards the end of this line, I introduced virtual hit ratios, where all guns would provide aiming information for every shot to determine whether or not their aims would have hit the target or not.

Series 4.x

This series focused largely on drive improvements, including improvements to the wave surfing drive, dive protection, and a new Ram Escape drive. This series also improved how fire power is selected.

Series 5.x

This series focuses on using a new strategy for calculating factors in guess factor guns and wave surfing drives, surfing multiple waves simultaneously (explored by never implemented), paying more attention to robot width, improving wall avoidance, and improving segmentation selection and processing.

Series 6.x

XanderCat series 6 focuses on taking everything learned so far and evolving it into a new set of components, or at the very least, cleaning up old components or features that did not work out. Series 6 introduces the new Evolution Drive, an updated Wave Surfing drive, and new ways of handling factor arrays.

Series 7.x

XanderCat series 7 uses the first release-ready version of the Xander framework. With the knowledge gained over prior versions of XanderCat, the Xander framework has undergone a final refactoring and cleanup and is now considered ready for public use. The Xander framework can be considered as version 1.0. In addition to using the finished Xander framework, series 7 may see updates to the main drive and gun, as well as a first release into the melee competition.

Series 8.x

This series will use my own take on using a K-nearest-neighbor (KNN) approach for the main drive and gun. It may also finally introduce surfing multiple waves at once.

My KNN approach to to create a KNN Factor Array Processor that can be used in both drives and guns. I already have a FactorArrayProcessor interface built into my guess factor / wave surfing framework that it will utilize. However, instead of saving a large number of factor arrays and combining them, it will instead store a tree of data points, retrieve the closest data points to the current situation, and build a single factor array from those data points. One advantage of this approach is that is should allow for a greater number of segmenters and slices per segmenter.

Series 9.x

This series uses the updated Xander framework version 2.0. There are a variety of changes as a result. Hopefully, some buggy areas will be improved. Some new features will be added.

Version 9.0

The changes in this version from previous are fairly extensive. Changes listed are just a quick summary.

Changes from previous version:

• Using Xander framework 2.0.
• Using Bullet Shadows in the main wave surfing drive.
• Various segmenter changes.

Version 9.0.1

Changes from previous version:

• Re-added x5 power selection from previous versions.

Version 9.1

Changes from previous version:

• Increase the ganularity of the drive segmenters.
  • Defender Speed Segmenter increased from 8 to 12 slices.
  • Bullet Travel Time Segmenter increased from 12 to 18 slices.
  • Attacker Bearing Segmenter increased from 10 to 12 slices.
  • Defender Acceleration Segmenter unchanged (3 slices).
  • Wall Smoothing Segmenter unchanged (4 slices).
• Re-added robot colors and changed color scheme a little.
• A few minor adjustments to maintain compatibility with some older versions of Robocode (for RoboResearch...yeah, yeah, I should just set up RoboResearch with a newer version of Robocode :-P)

Version 9.2

Changes from previous version:

• Replaced my old wall smoothing segmenter with a new wall stick segmenter. The new segmenter has the following advantages:
  • More slices. The old segmenter was fixed at 4 slices; the new segmenter has a variable number of slices.
  • Taking movement direction into account. The old segmenter looked at clockwise vs counter-clockwise; the new segmenter looks at forward vs reverse.
  • More efficient. The old segmenter used a robot predictor which was processing expensive; the new segmenter uses a simple wall stick approach that is quick to calculate.

Version 9.3

Changes from previous version:

• Started using bullet-hit-bullet as valid data points for the main wave surfing drive.
• Implemented improved algorithm for handling distancing. In addition to providing better overall distancing, this takes care of a recently discovered bug in the old system. The new system picks from a range of drive angles for distancing instead of having a fixed drive angle. For example, if the robot only has to drive a very short distance to reach the desired factor angle, it can choose to use a steeper advancing or retreating angle to get closer to the optimal distance (so long as it can still achieve the same desired facor angle).

Version 9.4

Changes from previous version:

• Replaced DefenderSpeedSegmenter with LateralVelocitySegmenter in the main drive.

Version 9.5

Changes from previous version:

• Switch to using my own scan from 2 ticks ago (instead of 1 tick ago) when creating opponent waves.
• Implemented form of surfing 2 waves at once. The surf selector will choose both a first and second choice for where to surf for the closest wave. From where each of those choices would position the robot, the first choice for the second wave will be considered. The first wave danger is added to the second wave danger for both the first and second choice. The drive will then use whichever choice had the lower combined danger value (see description at top of page for more detail).

Version 9.6

While rolling drive data in the past has provided dubious results, latest testing suggests that rolling drive data will have a positive impact. This version takes a first stab at rolling the drive data.

Changes from previous version:

• Now rolling drive data (previous there was no rolling at all). As currently configured, data point significance will drop in a linear manner with age, dropping to 1% of original significance after 1000 ticks. Data will never roll off completely; once significance has dropped to 1%, it will not drop any further.

Version 9.7

Changes from previous version:

• Fixed bug where robot history snapshots were not getting cleared out between rounds.
• Updated KNNFactorArrayProcessor to initialize with a linear point when used for a gun and no data is available (previously it would initialize with a head-on point).
• Fixed issue where multi-wave surfing was not being updated when bullet-hit-bullet eliminated a wave other than the next wave to hit.
• Changed gun so that aiming only occurs when gun heat is low.
• Updated multi-wave surfing so that multiple first wave points can be considered (currently using 6 points with minimum 1 robot width separation between each), rather than just a first and second choice.
• Changed wave weighting from equal to bullet damage / time until hit.
• Added flattener that engages whenever opponent hit ratio exceeds 12.5%. Will not engage until at least the 3rd round. This is still somewhat experimental, but initial test results are encouraging.

Version 9.7.1

• Relaxed flattener a little. Now engages at 13% hit ratio, and not until 4th round.
• Fixed issue with anti-ram and anti-mirror gun power selectors not honoring x5 requirements.

Version 9.8

Changes from previous version:

• Increase granularity on main drive segmentation:
  • Increased slices on bullet travel time segmenter from 18 to 24.
  • Increased slices on attacker bearing segmenter from 12 to 24.
• Change main gun segmentation:
  • Increased slices on defender speed segmenter from 8 to 16.
  • Increased slices on bullet travel time segmenter from 12 to 24.
  • Increased slices on attacker bearing segmenter from 10 to 24.
• Increase energy level to stop firing at from 0.1 to 0.5.
• Reduce default number of first wave surf position options from 6 to 5. (given current wave weighting, option 6 is almost never being selected)

Version 9.9

Changes from previous version:

• Updated distancing equation (techincally, I added and use a new SmartDistancingEquation that extends the original DistancingEquation). The original DistancingEquation is considered a Xander framework class, while the new SmartDistancingEquation is not.
  • Now takes wall proximity into account and will no longer recommend retreat angles when against a wall (as doing so can negatively affect the reachable range the drive uses).
  • Now behaves differently against top competitors.

Version 9.9.1

• Fix a couple of issues with the updated distancing.
• Reduce flattener engage percentage back to the original 12.5% opponent hit ratio (from 13%)

Version 9.9.2

• Turn flattener off. Once again, it has proved to be more trouble than it's worth.
• Improve how distancing determines if robot is against a wall.

Version 9.9.3

• Turn flattener back on. Flattener now engages at 12.5% opponent hit ratio, but only if my own hit ratio is under 12%.
• Added saving of certain battle statistics to file. This is used only for performance analysis; it is not used by the robot for in-battle tactics. Currently saving hit ratios and some flattener info.
• XanderGun now reduces fire power to 1/3 the normal level when robot energy drops below 7.

Version 9.9.4

• For the flattener, instead of requiring my own hit ratio to be under 12%, instead require that my own hit ratio simply be less than the opponent hit ratio.
• Remove the robot energy 1/3 power when robot energy is below 7 adjustment.
• When not "for real" aiming due to gun heat, point gun directly at opponent to keep it in the generally correct direction.
• Power selection now reduces power to slightly less than what opponent is using when both self hit ratio and opponent hit ratio are very low (try to let the opponent run itself out of energy before us).
• Implement factor array caching in the KNNFactorArrayProcessor. This should improve overall drive efficiency, especially with the multi-wave surfing.

Version 9.9.5

• Fix issue where power selector could try to fire power 0 bullets (bug introduced with a change in 9.9.4).
• Add new and improved bullet-shielding protected gun. Take that MoxieBot!
• Stop logging no-fire forced energy drains as opponent bullet waves (a minor issue, but needed to be fixed for the new bullet-shielding protected gun to function properly).

Version 9.10

• Fixed significant bug in how drive data is rolled with age. This may have been a "performance enhancing bug", as my drive isn't perfected yet and the bug gave the drive data more randomness. With the bug fixed, it will take a significant amount of new analysis before the drive parameters are properly re-tuned.
• Improved ram escape drive. APS should be about the same against some of the trickier rammers like xbots, but should increase by a reasonable margin against some other rammers such as RedBull.
• New Drive Array added to further improve scores against simple targeters. Drive array includes Anti-HeadOn drive, Anti-Linear drive, Anti-Circular drive, and the main drive. Drives other than the main drive are only used so long as the opponent hit ratio against them remain very low. Some comments on each:
  • Anti-HeadOn Drive -- not expected to improve score overall, as the main drive handled head-on targeters just fine, but this will drop CPU usage a fair amount against head-on targeters.
  • Anti-Linear Drive -- The main drive does a fair enough job against linear targeters, but this drive does better. Several APS increase against linear targeters expected.
  • Anti-Circular Drive -- The main drive has a harder time with certain circular targeters. APS increase could be as high as +15 in some cases. However, the number of cases where this will apply is expected to be very low.
• Now rolling gun data when my hit ratio is below a certain threshold.

Version 9.10.1

• Disable drive array. This should stabilize the robot until certain other parameters can be adjusted, and will also help indicate if the new drive array is hurting more than it is helping (it definitely helps against some robots, but could it be hurting overall?)

Version 9.10.2

• Increase data roll rates.
• Minor tweak to low hit ratios power selection.

Version 9.11

Changes from previous version:

• Slight refactoring to allow same data logging system to be used with multiple factor array processors with different parameters.
• Take first stab at dynamic drive data rolling.
• Remove special low-hit-ratio power selection routine due to poor performance.

Version 9.12

Changes from previous version:

• Make dynamic drive data rolling a linear effect, instead of the more crude on/off approach.

Version 9.13

Changes from previous version

• Minor tweak to Ideal Position Drive so that it keeps robot a little further away from opponent when attempting to drive past opponent.
• Double the granularity of drive segmenters for bearing and bullet travel time.

Version 9.14+

All versions from 9.14 through the end of the 9.x series are alpha and beta tests for series 10.x. Refer to Version 10.0 notes for an idea of what these versions may include.

Series 10.x

The "Pro" series.

Version 10.0

Changes from previous version:

• Switch to using a true KD Tree for managing drive and gun data. KD Tree from Simon D. Levy at the Washington and Lee University in Lexington, Virginia.
  • Gun set up to use k-nearest neighbor data selection.
  • Drive set up to use ? -- currently exploring using straight k-nearest neighbor, or k-nearest neighbor on visit data and using max distance from the visit data to do a distance search for hit data; also considering using range search still.
• Remove bullet travel time segmenter and reverse direction wall stick segmenter from the drive.
• Fix massive bug in my Bullet Travel Time Segmenter. This bug has surprisingly been around for a long time, and was rendering the bullet travel time segmentation ineffective for the drive. However, since this segmenter has been removed from the drive, this change will have no impact.
• Fix bug in AbstractSegmenter (the base class for most of my segmenters) that was causing dimension values to fall out of the proper range for the KD Tree (note: it sounds a little weird to have a bug fix related to the KD Tree when the KD Tree is listed as new to this version; this is because the final versions of the 9.x series used the KD Tree as beta tests for the upcoming 10.x series, but I didn't want to officially list the KD Tree as a feature until this version).
• Minor refactoring of Guess Factor and Wave Surfing components to better separate responsibilities and allow for better caching.
• Implement virtual gun array. Currently 3 guns, each being a guess factor gun but with slightly different parameters on how to surf the data. This takes advantage of the better caching, as each gun uses the same caching log reader, meaning each gun after the first uses a cached copy of the nearest neighbor search results.
• Implement drive array. Currently 2 drives, a targeting detector drive and the main wave surfing drive. Targeting detector drive is only used so long as it's hit ratio is lower than the main drive ratio, and that ratio stays under 8%.
• Implemented more aggressive energy conservation at low energy levels.
• Opponent hit ratios against specific drives are only updated if the active drive had at least 5 ticks to react to the wave. This prevents penalizing drives for getting hit by close range shots.