Talk:XanderCat

Congrats on breaking the 50% barrier. Seems that you have the planning of your bot on scheme, now it's just the translation into the right code. One small remark: You don't have to have 'zillions of versions' present in the rumble, the details of older versions still are available when not in the participants list anymore. Comparisons between two versions are quite easy to do like [1] . Just click on your bot in the rankings, then the details and a few older versions are shown. Good luck with your further development! --GrubbmGait 08:37, 25 May 2011 (UTC)

Thanks GrubbmGait, though I'm not sure how much praise I deserve for being officially average. :-P I'm trying out a slightly revised version today, version 2.1. No major component changes, but it modifies the bullet firing parameters, driving parameters, some segmentation parameters, and has improved gun selection. Skotty 20:43, 25 May 2011 (UTC)

Version 3.1

Interesting results for version 3.1. No real change in rank from 3.0, but using an entirely new drive. I've done away with the borrowed wave surfing drive from BasicGFSurfer and replaced it with a drive of my own design.

Despite the new wave surfing drive (which I will call a Stat Drive) which I crafted almost entirely from scratch, I think it shares a lot in common with other wave surfing drives. It's just naturally where you end up when working out the best way to drive. I really haven't tried to tweak the segmentation yet, so I think it can be further improved with a few parameter changes.

Here is what my new drive does (you will likely see a lot in common with other drive strategies out there):

• Segmentation - Much like other wave surfing drives, my Stat Drive supports segmentation. I can't remember what it is actually segmenting on right now (don't have the code in front of me at the moment). I'll add that detail later. It is very easy to change the segmentation parameters. The Stat Drive relies on a seperate component to determine the segment or combination of segments, and the segmenters can be swapped in and out easily.
• Tracking danger - Each segment has a fixed number of "buckets" or "bins" that represent the danger at a particular "factor", where a factor represents an angular offset of the robot from an original bearing of the bullet wave origin to the robot at the time the bullet was fired. When a particular factor is determined to be more dangerous, a value is added to the corresponding bin or bins around that factor. Initially when I wanted to add danger, I just added to one bin. One thing I did steal from from the BasicGFSurfer wave surfing drive was the manner of adding danger to all the bins, trailing off sharply from the most dangerous bin. I don't know why I didn't think to do this initially. Once my eyes glanced over it, it was obvious it was what I should have been doing from the start.
• Bullet Hits - The most dangerous of events -- actually getting hit by a bullet. When hit by a bullet, the Stat Drive records danger of a certain amount (lets say a value represented by the variable d) to the matching bin of corresponding segment. One tenth that amount (d/10) is currently added to all other segments, though this is just experimental; I may modify or remove that effect as I tune it a bit more.
• Wave Hits - When a wave hits (but not necessarily a bullet hit), the Stat Drive currently records one fifth the amount of danger (d/5) for the matching bin of the corresponding segment. Thea idea being that the opponents gun, likely being a "Guess Factor" gun, might be more likely to aim for that bin next time, so lets try to avoid it. This also probably needs some fine tuning. Part of the same experiment as with bullet hits, adding one tenth of that amount (d/50) is added to all other segments.
• Wall Avoidance - While I wrote it from scratch myself, wall avoidance right now is doing pretty much the exact same thing as the "wall stick" approach. I have some ideas that would be fancier, but the "wall stick" approach works for now.
• Rolling danger - Rolling danger is the idea of removing danger previously added from bullets or waves that are over a certain age. The Stat Drive is not doing this right now, but I'm planning on experimenting with the idea.
• Figuring out where it can get to - One of the first steps to avoiding a bullet wave is determining how far you can go in each orbital direction before the bullet hits. At first I used some crude approaches to this with the Stat Drive, but they just won't cut it if I want to be really competitive. I now have it predict our position into the future, taking pretty much everything into account (turn rates, acceleration/deceleration rates, wall smoothing, etc) to make the prediction as accurate as possible.
• Figuring out where to go - once we know how far we can go, we have to decide where in that range we want to go. I'm experimenting with a few approaches. For now, it looks for the bin with the lowest value and heads there.
• Figuring out how to get there - Once we know where we want to go, we have to figure out how to get there. This seemed simple enough, but one problem I ran into was overshooting the target and being in the wrong place when the bullet arrives. This problem turned out to be significant in my testing. So I had to do additional work to ensure that if I will reach my target before the wave hits, I slow down before getting there so I land right on target. This sounds easier than it actually was to implement.

Where to go from here?

Performance was roughly equal in the rumble to the BasicGFSurfer drive. I need to tweak the segmentation approaches and parameters. I need to tweak the manner of adding danger. And I need to play around with rolling danger to see what effect that has. Once that is done, I don't believe I will make any more changes to the Stat Drive or it's use in XanderCat.

I may employ other drives in combination at some point using a "drive selector", an ability that is built into the Xander framework. For example, I would like to build a drive and gun built specifically for "mirror" bots that mirror their opponents drive; the drive selector would switch to these components whenever a mirror bot is detected.

Outside of drives, my Stat Gun is still a bit crude. I know I can improve there. And then I also have a few other little tricks up my sleeve I would like to try when I have the time.

It's neat to see you taking such a systematic approach with robocode! If I may a few suggestions:

• If I understand correctly, you add d/10 danger to every bin (except the one that hit you) rather than (in addition to?) adding bin-smoothed danger to each bin. I don't think this will help anything. The bin-smoothed danger should be enough.

• Logging hits from every wave, regardless of whether the other robot hit your robot, will give you a flatter movement; however, you may not actually want a flatter movement, even against GF guns. Before wave surfing was invented, I imagine that GF guns didn't roll their averages very much. Because of this, a flat movement will be worse against these guns. Rather than giving the enemy a flat movement to shoot at (which will make their targeting very close to random), you should move to the same GF repeatedly. When they hit you there, you know there is a peak in their stats, so you move somewhere else, and hopefully they keep shooting there for a while, allowing you to dodge bullets. Did I explain that well?

(I had thought of doing something like that but didn't for the reasons described above. It sounds rather similar to YersiniaPestis, but without the adaptive weighting of the flattener.) --AW 19:52, 6 June 2011 (UTC)

Nice job! Implementing Wave Surfing correctly can be a huge undertaking. My first suggestion would be to try just disabling the "every wave" logging of hits. You're right this should make you more unpredictable to learning guns. What most of us have found is that straight dodging from bullet hits actually works better against the vast majority of guns - only against the best guns does a "flattener" (what we call that mode) help. But more importantly, a flattener also destroys your scores against simple targeters.

I see you're getting 80% vs Barracuda and 88% vs HawkOnFire. Those could both be over 99% with no segmentation. My best advice would be to work on distancing, dive protection, and ironing out bugs until you can get that before trying to refine other aspects. Working on other stuff will only make it harder to fix the core stuff, and you may have to re-tune everything anyway once it's fixed. (Just turning off the flattener may go a long way!)

Good luck! --Voidious 20:37, 6 June 2011 (UTC)

Thanks for all the suggestions. I've been intentionally trying to come up with a lot of the ideas and code myself, as that makes it more rewarding for me. On the down side, this has made it harder to learn all the terminology used by the Robocode community. Not until both of your comments did I know what a "flattener" was, though I had seen the term pop up here and there. I hadn't spent too much time thinking about what the effects of it would be against different opponents, but your comments give me food for thought. I actually have my system set up now to run different configurations of my robot against a test base of robots, so I am now at the point where I can see some real results rather than just trying to deal with the theoretical. I'll try turning off the flattening and see what happens. Skotty 22:18, 6 June 2011 (UTC)

I assume by "distancing", you mean trying to keep my robot a reasonable distance away from the opponent. I was thinking maybe try to refine my drive path so that it will move slightly away from the waves if the wave origins are too close, and possibly favoring non-smoothing directions when near a wall and the calculated danger in each direction is similar. "Dive protection" as I understand it is not driving towards the enemy excessively; I don't see how this would happen except to a limited degree when wall smoothing, or on startup before bullets start flying (at the moment, when no bullet waves are in action, XanderCat will just move in a straight but wall-smoothed path, causing it to circle around the edges of the field; I should probably change this to make it move into a more desireable position before bullets start flying, rather than relying on chance). Skotty 17:46, 7 June 2011 (UTC)

Version 3.2

Had a bad night of tweaking where everything I did seemed to make my robot worse. I've turned off the flattening but I don't think I have a proper test bed of opponents to determine what kind of effect it might have. It did increase the score on Barracuda and HawkOnFire, but only to the about 90%. I did, however, finish some new anti-mirror components. PolishedRuby 1 is soooo dead. :-D I haven't tested against any other mirror bots yet, but my tests against PolishedRuby put a big smile on my face. As you might guess, when mirroring is detected, I have a drive and gun that work in tandem, where the drive plots a semi-random route in advance that the gun can process to fire on the mirror of the future positions. Awesome. My framework makes it easy to add it on to any existing gun combinations. It's not perfect, but it gets the job done, and might can be improved a bit more. With the mirror components active, my gun hit ratio on PolishedRuby jumped from something very sad up to a wicked 70%.

I've got my score on Barracuda up to the low 90s, and HawkOnFire up to about 98%. I've disabled the flattening, and I've implemented a new drive that takes command on the first few moments of a round to try and obtain better positioning before bullets start flying. Also, my StatDrive will now change it's angle a little to back away from waves when it deems itself too close to them. I also have the anti-mirroring operational. I was going to try and update my StatGun for this version (3.2), but I think I may hold off on that until version 3.3. I want to see what effects the changes so far have made.

Rumble Results

Fascinating results in the rumble. Despite winning fewer rounds than version 3.1, version 3.2 ranks about 30 places higher. Presumably by beating the simpler robots by quite a bit more than previously. Lots of variations in the PBI. I'll have to play around with some of the ones version 3.2 performed poorly against. I'll probably come up with a way to turn the flattening on and off automatically, which I think some of the other robots do. Only other thing I can think of to do for driving is to put some work into not running into the opponent robots, which is something I have ignored previously. AntiMirror components rocked.

Next version I will update the StatDrive. I know of a couple of ways it could be reasonably improved. And after that? Not sure...

My suggestion is that you need to up your score against Barracuda - there are still lots of points to be gained there. Until you are getting 99+% you are losing points due to not getting far enough away. If you watch your battles against Barracuda note every bullet hit and think about what your bot could have done differently to avoid it, be it reversing, being further away, not being against a wall, etc and then code something to get it to (not explicitly, but generally) avoid that situation next time. I'm not sure how your drive system works but in my bots I modify the desired angle towards the orbit centre proportional to the distance from the orbit centre, so as it gets farther away it moves towards the centre, and as it gets closer it moves away. Anyways, some food for thought. --Skilgannon 08:58, 8 June 2011 (UTC)

Were you looking at version 3.2 or 3.3? Version 3.2 gets about 93% against Barracuda. Yeah, it could be better. Version 3.3 in the rumble only got 80% against Barracuda. I can't explain that. I've run 3.3 myself against Barracuda many times, and it always gets around 93%, same as version 3.2. Ignoring that anomaly, where is that other 7%? It may be from collisions. Right now, XanderCat ignores collisions with the opponent, and can get stuck rammed against them. Also, it may be from getting too close when wall smoothing. I had mentioned the possibility of moving away from the wall in cases where danger each direction is similar in order to not get jammed against the wall as much, but I haven't implemented that idea yet. Skotty 14:21, 8 June 2011 (UTC)

I'd suggest hunting for bugs really. Even 98% against HawkOnFire, is low enough that I think that notable surfing bugs could be likely, (and having a large hidden influence against other bots). It should be possible to get to 99.9% or so if the surfing algorithm is reasonably precise and the bugs of implementation are worked out. --Rednaxela 14:48, 8 June 2011 (UTC)

Version 3.4 moves up the ranks, but still gets 98% on HawkOnFire and 95% on Barracuda. I believe this is due to not having any dive protection when wall smoothing (I do employ distancing, if I understand correctly what this is -- attempting to back away some when in too close -- but this doesn't help if you are getting smoothed into a wall). I'm still working on a good solution for dive protection near walls. I tried a few things when developing version 3.4 but haven't come up with something that improves performance yet. Perhaps for the next version. -- Skotty 17:16, 9 June 2011 (UTC)

A quck note for you in relation to ucatcher. That bot is uses bullet shielding. Basically, the better you shoot at it, the better chance it has to deflect your shot. Not too hard to detect when it happens either, just check the bulletHitBullet event and see if it happens a bunch. If so, don't aim for the center of the bot, but an edge of it instead. --Miked0801 23:31, 10 June 2011 (UTC)

Version 3.6

Interesting results in the Rumble. Compare this version to version 3.4, and check out the PBI graph. It seems I inadvertently tuned it against top bots, but somehow lost a bunch of points on the middle of the pack. With a little more analysis and testing, I think I can finally jump up in the ranks again. I suppose there could still be some hidden bugs I need work out, too. The drives on 3.4 and 3.6 are the same but the gun on 3.6 is far more advanced. It should be notably higher in the ranks. Oh well. I guess I have to make version 3.7 before taking a break now. :-)

PBI

Okay, with version 3.8, I am frighteningly close to being able to tie or even beat some of the top and famous robots (note that I haven't been using flattening either), yet I am still way underperforming on the middle of the pack. Crazy! One problem being that apparently my small test bed of robots is not properly representative of the whole. I guess I need to go round up some problem bots for me and figure out what gives. Skotty 23:53, 12 June 2011 (UTC)

One tip: when trying to improve against certain bots, make sure you run a lot of battles of your previous version against those bots, too. It takes hundreds of battles to get a real accurate result in any pairing, so the rumble result isn't really gospel. You can easily find yourself chasing phantoms (mistaking bad luck for underperforming). --Voidious 00:02, 13 June 2011 (UTC)

A remark about version 4.0. Your wrapper against bullet shielders does have a very big offset. I use fixed 0.6 distance either way and my bullets are only occasionally intercepted. Your offset of 5 or 10 does influence your performance against the 'pack' to much. There are a lot of bots out there that give you a hard fight although ranked lower, as they do not squeeze every percent out of the minor bots. Compare your stats against a bot on a rank you wish to have, see your strengths and weaknesses compared to it and handle accordingly. --GrubbmGait 22:48, 15 June 2011 (UTC)

The bullet shielding effect only engages if there are a set number of consecutive bullet-hit-bullets, so I think I'm okay on most of the pack. It would only happen by rare chance against a non-bullet-shielding bot (or so my theory goes). Skotty 23:43, 15 June 2011 (UTC)

From Robin

Holy Disco Batman, I'm stuck in the 70's!

HOT vs RamBots

He's no longer in the rumble, but there's a bot that might make you think twice about using HOT vs RamBots: MaxRisk. =) --Voidious 20:07, 21 June 2011 (UTC)

Ramming messes with all my hit ratios, which was making the gun selection almost random against them, and occasionally XanderCat would miss a shot against a rammer follwing almost directly behind (probably due to a guess factor shot). This is why I added the extra decision to only use Head-On targeting against rammers (and note, the head-on targeting only takes effect when opponent is within very close range). I'll have to check out the bot you linked to see what it does. At very close range, I don't see how head-on could be a bad choice. At distance while they are closing, yes, head-on might not be best. But at distance, my regular gun selection is active. This makes me think, however, that I could be doing something better when the rammer is at distance, as my regular gun selection, as previously mentioned, is usually messed up by the wild hit ratios that occur when the opponent is constantly ramming.

I haven't seen MaxRisk in battle for a while. But at the time he was released, Dookious was using HOT as part of his anti-ram mode and MaxRisk crushed him into little pieces. I think the issue is that MaxRisk uses prediction, so he's ramming the spot you're moving towards, not just heading straight at your current position. --Voidious 17:35, 22 June 2011 (UTC)

Rethink / XanderCat 4.8+

I lost some ranks when I refactored the guess factor and wave surfing code in version 4.7, and have yet to get them back. But I'm still convinced the refactor was a good thing.

I've ironed out all the major bugs, and if I watch XanderCat in some battles, I don't see it doing anything obviously wrong. This got me thinking about how I handle segmentation again. I think my philosophy on balancing segments for comparison was wrong in the drive, and am changing it in version 4.8. I also plan on excluding certain segment combinations that when I think about them, just don't make much sense (like using just opponent velocity). I think this should improve performance.

Beyond this, I'm not sure what I would do next to try to improve. I could run zillions of combinations of segments and parameters just to see what seems to work better against a large groups of robots that I think is representative of the whole. Not sure I will go to that extent though. Skotty 01:09, 22 June 2011 (UTC)

I'd definitely say that you still have non-negligible bugs / issues with your surfing. Looking at Barracuda and HawkOnFire again, compared to DrussGT we have 95.82 vs 99.83 and 97.91 vs 99.91. In other words, both are hitting you ~20x as much, totally unrelated to how you log/interpret stats (because they're HOT). Not to be a downer - XanderCat is coming along great and you appear to have a really robust code base. Or if you're burning out on 1v1, how about Melee? It's a much different animal. =) --Voidious 01:28, 22 June 2011 (UTC)

It appears as though I'm on the right track with version 4.8. Just for you Voidious (grin), in addition to other changes, I configured it to maximize scores against head-on targeters, which raised the Barracuda and HawkOnFire scores to 98.98 and 98.76 respectively (2 battles each so far). To get the rest of the way to DrussGT levels, I will need to tweak my dive protection a little more; it still causes XanderCat to stall near a wall long enough to be hit every once and awhile. I may need to also tweak my "Ideal Position Drive" a bit more too, as it still drives too close to opponents occasionally when trying to reach an ideal position (the Ideal Position Drive drive runs at the start of each round before bullets start flying).

Nice. =) For better or worse, the RoboRumble greatly rewards bots that can annihilate HOT and other simple targeters, so you might be surprised by how much of a ranking increase you can find by polishing that aspect of your surfing. It's not always the sexiest thing to work on, nor the most fun... But more importantly (to me), it's just a good way to verify that your surfing is working how it should. I can't find a good quote, but both Skilgannon and Axe have commented on the fact that if even a single HOT shot hits you, there's something wrong. --Voidious 17:51, 22 June 2011 (UTC)

Nice work, but just as a note, some might think me crazy, but I don't think *any* explicit dive protection is necessary for this sort of thing really. My surfing bots RougeDC and Midboss (same movement code), get 99.5% against HawkOnFire with no explicit dive protection whatsoever (and in certain past versions they did even better IIRC). The thing is, as I see it, dive protection is completely unnecessary if the surfing properly considers how movement changes botwidth. I much prefer it that way as it doesn't require tweaking/tuning to get right. Just my 2 cents on dive protection. --Rednaxela 20:50, 22 June 2011 (UTC)

Well, I'd still call it "dive protection". =) But yes, I agree that multiplying danger by bot width (or dividing by distance, which I think is still what I do) is about the most elegant solution. And I doubt anyone's calling you crazy. Do any top bots since Phoenix use special cases? I guess I'm not sure about GresSuffurd or WaveSerpent. --Voidious 21:14, 22 June 2011 (UTC)

Oops, I guess I'm out of touch. Diamond still has special cases, despite taking this approach - it scales the danger more than linearly beyond a certain threshold, as Dookious did. Maybe I'll test removing that, just for the sake of argument. =) I think it will lose points, though. Sure, for one bullet, the danger scales linearly with bot width. But that bot width affects future waves too. I suppose whether this is "explicit dive protection" would be up for debate. --Voidious 21:24, 22 June 2011 (UTC)

Hmm...considering my own robot width when surfing...why didn't I think of that before? Guess what new feature will be in version 5.0? :-D Skotty 22:44, 22 June 2011 (UTC)

Rather than multiplying danger by bot width, I prefer integrating over the affected bins, since many bins can be covered at close range... ;) --Rednaxela 22:49, 22 June 2011 (UTC)

GresSuffurd has 2 lines of code handling both distancing and dive protection. This code hasn't been changed for years. The dive protection just handles the angle, not the danger. My latest effort was to use the summed danger of all covered bins instead of the danger of one bin to decide which direction to go(forward, stop, backward), but this approach let me fall out of the top-10 ;-) Sometimes a simple, proven, not optimal solution works better than a theoretical optimal solution. I do like the idea of letting danger instead of angle decide when to change direction though, and I will continue in this path with the next versions. Welcome to the dark caves of Robocode. --GrubbmGait 23:25, 22 June 2011 (UTC)