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My first truly competitive robot, it was written for a contest at school (which I won, btw). It's a massive, multi-mode robot with just about everything you could imagine, in either working or not-quite-working form. I developed 9 movement patterns for it (one of which doesn't work), 7 aiming algorithms, 2 types of radar control (spinning for melee and tracking for 1-on-1), and 5 target-choosing algorithms (for melee, one seems to not be very effective, others do well depending on the nature of the competition). Each of the above modes is its own class, which extends one of the children of the Part class. The PartSelector? class was written as a generic aggregation of Parts, and there are 4 subclasses of that, which are aggregations of movement strategies, target choosers, aiming algorithms, or radar controls. All in all, it gets fairly complicated, but it's really easy to expand :-) (which I like). Next goals are to make my anti-gravity work somehow, and maybe add a few more kinds of pattern matchers and a curve-flattener to counter GuessFactorTargeting. Eventually (I've decided), it will also beat a select group of "good" robots, at which point I'll call it version 1.0.


How does it move?

Hahaha! Well, it has 9 movement patterns:

How does it fire?

It selects the best of 7 virtual guns for each robot, firing a virtual bullet just about each turn toward each robot (that's why big melee battles get really slow with this robot):

How does it dodge bullets?

It moves around in 9 different patterns (well, 8, and a couple fewer, depending on the nature of the battle) to screw up GuessFactorTargeting and PatternMatching. One of its movements, however, is specifically designed to (semi-randomly) dodge direct, circular, and linearly aimed bullets. See the section on movement above.

How does the melee strategy differ from one-on-one strategy?

It picks a different movement pattern depending on the size of the battle. At the moment, it never picks anti-gravity, but if it did, it would likely use it primarily (maybe only) in melee. It chooses from spiral, wall, oscillating, corner, complex oscillating, or bullet dodging in Melee battles, and it chooses between spiraling, wall, oscillating, random, magnet, complex oscillating, and bullet dodging for OneOnOne battles (or Melee battles where everyone has already been killed off except myself and one other). Eventually, I would like to be even smarter in OneOnOne and detect if my opponent has no aiming, or if they rely heavily on circular or linear aiming. Against HeadOnTargeting, I could use spiraling, walls, and bullet-dodging, and against linear/circular targeters, I could use oscillating, corner (which also oscillates), random, complex oscillating, and bullet-dodging techniques.

How does it select a target to attack/avoid in melee ?

Well, since nothing got left alone in this robot, it also has 5 ways of choosing a target in Melee battles, depending on its win-loss record with each one:

What does it save between rounds and matches?

It stores all information about the enemies, including the stat-buffer and pattern-buffer, as static variables. It also maintains all the part-selectors, which includes experience with movement patterns, virtual guns information, etc. as static variables. Currently, it doesn't store any information to disk, although it may be beneficial to store information about which guns are more effective to use and which movement patterns get me hit less by each enemy.

Where did you get the name?

The design of the robot is modular enough that I thought of it as being built from a bunch of "parts" that I found lying around in my mind or on the Internet. Just a bag of Spare Parts all thrown together into one gigantic robot.

Can I use your code?

Go for it. Most of the part classes should be easy enough to figure out and move over to your own robots. As only a few of the parts are truly my own, I can't get mad at you for stealing them from me. I suppose if you based a robot on one of those parts, though, you could dedicate the robot or a song or something to me.

What's next for your robot?

Get the anti-gravity thing to work, make a statistical flattener (I like to call it a SandboxFlattener), possibly add a more Aspid-style pattern matcher and a more iiley-style pattern matcher at some point.

What other robot(s) is it based on?

All of them! Among others, I got ideas from discussions on this wiki, from DuelistNanoMelee, my own CircleBot, Walls, MogBot, SandboxDT, and a lot of other worthy robots.

Question department

Wow, congrats on winning that competition! Is this bot uploaded to the repository yet? I was trying CurveFlattening with Marshmallow and it worked quite well, but I have now switched to using random, since it flattens the curve quite well. -- PEZ

Yes, SpareParts is available at the repository as of yesterday. I also have a version of SpareParts with sound that taunts its enemy when it wins using Mortal Kombat sound clips. The repository won't let me upload it, though, unfortunately, as it is nearly 2 MB (It was a large robot without the sounds packaged into it). I think I'll put it somewhere and link it from the repository. -- Kawigi

I can't run it on my computer though. Maybe it doesn't work on 1.3.1? I'll run it on my computer at work which has 1.4.1. It should be interesting to see it's VirtualGuns against Marshmalow?s' dittos. Where have you read about SandboxDT's statistical guns? I'd very much would like to read about it. It's amazingly effective even from the first bullets fired! You can upload the sound version on this wiki if you like. Check the Uploads page for details. -- PEZ

Paul Evans talks about how his gun basically works on his webpage, the page is linked from the wiki page for GuessFactorTargeting. My impression is that David also has a good grasp on them. As for versions of Java, I didn't know I had anything on there that required 1.4, but then again, I don't know where the geom classes fall, and I always use the 1.4 docs and JVM, whether at school, or work, or home. -- Kawigi

Get the [sound version] here

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Last edited April 27, 2003 7:54 EST by Kawigi (diff)