Difference between revisions of "Sunderer"
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| targeting = [[Linear Targeting]] and [[Head-On Targeting]] | | targeting = [[Linear Targeting]] and [[Head-On Targeting]] | ||
| movement = [[Oscillator Movement]], [[Ramming Movement]] | | movement = [[Oscillator Movement]], [[Ramming Movement]] | ||
| − | | current_version = 1. | + | | current_version = 1.19b |
| released = 2023 | | released = 2023 | ||
| license = [[RWPCL]] | | license = [[RWPCL]] | ||
| − | | download_link = | + | | download_link = https://github.com/ersamson/robocode/raw/main/ers.nano.sunderer.Sunderer_1.19b.jar |
| isOpenSource = true | | isOpenSource = true | ||
| isMelee = false | | isMelee = false | ||
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''' How competitive is it? ''' | ''' How competitive is it? ''' | ||
| − | Currently ranked # | + | Currently ranked #9 (9-12?) in NanoRumble, #43 in MicroRumble |
== Strategy == | == Strategy == | ||
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'''How does it fire?''' | '''How does it fire?''' | ||
| − | It uses an "Averaged" Linear Targeting. It's basically a normal linear targeting but also gets another velocity data point when it fires ( | + | It uses an "Averaged" Linear Targeting. It's basically a normal linear targeting but also gets another velocity data point when it fires (at "max gun heat") then just divides those two velocities into two. When in Ram mode, it becomes the vanilla linear targeting as the "max gun heat" velocity is forcibly equated to the current velocity of the opponent. |
'''How does it dodge bullets?''' | '''How does it dodge bullets?''' | ||
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'''What's next for your robot?''' | '''What's next for your robot?''' | ||
| − | I'm quite happy | + | I'm quite happy to be within Top 10 in NanoRumble, let's see what the future brings. Though, I'll definitely update code comments and do a little clean up in the near future. |
'''Does it have any White Whales?''' | '''Does it have any White Whales?''' | ||
Latest revision as of 15:48, 25 November 2023
| Sunderer | |
| Author(s) | User:ersamson |
| Extends | AdvancedRobot |
| Targeting | Linear Targeting and Head-On Targeting |
| Movement | Oscillator Movement, Ramming Movement |
| Released | 2023 |
| Current Version | 1.19b |
| Code License | RWPCL |
| Download | |
Background Information
What's special about it?
It's does not use Pattern Matching and the Lateral Linear Targeting is a bit 'different.' It does Ram the opponent when it 'logically' feels like losing. Created with great appreciation to the culmination of the work laid out by former and current Robocode authors.
How competitive is it?
Currently ranked #9 (9-12?) in NanoRumble, #43 in MicroRumble
Strategy
How does it move?
It pretty much has three modes in total. First mode a basic One-Way Oscillation Movement. Second is a Two-Way Oscillation movement which detects an energy drop and changes direction. Finally when all movement strategies fail, it turns to Ramming movement.
How does it fire?
It uses an "Averaged" Linear Targeting. It's basically a normal linear targeting but also gets another velocity data point when it fires (at "max gun heat") then just divides those two velocities into two. When in Ram mode, it becomes the vanilla linear targeting as the "max gun heat" velocity is forcibly equated to the current velocity of the opponent.
How does it dodge bullets?
Only the Two-Way Oscillation has a 'feeble' attempt in dodging bullets through detection of the opponents' energy drop and changes direction.
Additional Information
Where did you get the name?
From Planetside 2, the Sunderer is called the "battle bus" there.
Can I use your code?
All good!
What's next for your robot?
I'm quite happy to be within Top 10 in NanoRumble, let's see what the future brings. Though, I'll definitely update code comments and do a little clean up in the near future.
Does it have any White Whales?
Foilist in particular. But generally weak to Pattern Matching and John Cleland's Predictive Rolling Average Linear (PRAL) gun.
What other robot(s) is it based on?
This took lots of ideas from Yatagan, NeophytePRAL and especially Sabreur.
And of course, even if I'm "late in the game" I'd still want to give a huge thank you to all the contributors on the wealth of information on both Old and Current RoboWiki.
