XanderCat

XanderCat
Author(s)	Skotty
Extends	AdvancedRobot
Targeting	GF / Linear / Circular / Anti-Mirror
Movement	WS(Hybrid) / Anti-Mirror / RamEscape / IdealPosition
Released	2011-5-20 (v 1.0)
Best Rating	#42 (v 6.8)
Current Version	8.3
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, 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 required).

Best against: Any robot that spends too much time standing still, going straight, going in circles, or doing basic mirroring.

Worst against: Nothing specific, but still need to improve against the middle pack.

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.

XanderCat 9.0 utilizes the following component chain: 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 --> Virtual Hit Ratio Gun, Direct Wave Surfing Drive

             ___________|____________
            /           |            \
 Guess Factor Gun   Linear Gun   Circular Gun
                                   

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


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

Gun

Gun Peak

Drive

Drive Peak

Drive Array Select

Drive Hit Logging

Drive Predictions

Drive Adjustments

Drive Rolling Avgs


6.5

1.01

13.41, 8.77, 8.41, 7.15, 6.94

0.21

7.70, 7.61, 6.93, 6.93, 6.49

1.19 (5.53 peak)

0.02 (0.04 peak)

0.88 (6.77 peak)

0.09 (1.51 peak)

0.07 (0.89 peak)


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, 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 (In Development)
Changes from previous version:
*  Using Xander framework 2.0.
*  Using Bullet Shadows in the main wave surfing drive.
*  Various segmenter changes.