Difference between revisions of "Pris"
Darkcanuck (talk | contribs) m (updated scores) |
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| Line 4: | Line 4: | ||
| extends = [[AdvancedRobot]] | | extends = [[AdvancedRobot]] | ||
| targeting = [[Neural Targeting]] (GF) | | targeting = [[Neural Targeting]] (GF) | ||
| − | | movement = [[ | + | | movement = [[Neural Surfing]] |
| released = June 2009 | | released = June 2009 | ||
| − | | rating = | + | | rating = 74th (72.4 APS) |
| − | | current_version = 0. | + | | current_version = 0.84 (dev) |
| license = closed | | license = closed | ||
| − | | download_link = http:// | + | | download_link = http://darkcanuck.net/rumble/robots/darkcanuck.Pris_0.84.jar |
| isOneOnOne = true | | isOneOnOne = true | ||
| isMelee = false | | isMelee = false | ||
| Line 30: | Line 30: | ||
; How does it [[Movement|move]]? | ; How does it [[Movement|move]]? | ||
| − | + | The latest version implements [[Wave Surfing]] with a neural network to store danger values. It appears to provide fast learning, while giving "standard" targeting methods a tough target to hit. There is still lots of room for improvement here, I've barely scratched the surface on this new strategy. | |
| − | |||
| − | |||
| − | |||
| − | |||
; How does it fire? | ; How does it fire? | ||
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; What does it save between rounds and matches? | ; What does it save between rounds and matches? | ||
Between rounds, saves all neural network weights and targeting stats. | Between rounds, saves all neural network weights and targeting stats. | ||
| − | |||
| Line 59: | Line 54: | ||
; What's next for your robot? | ; What's next for your robot? | ||
| − | * | + | * Bullet power selection is an area that needs more research, so I'd like to look into using [[Reinforcement Learning]] to generate a heuristic for selecting the right power. |
| − | + | * It would seem appropriate for Pris to have a ramming mode (minus cartwheels)? | |
| − | * | ||
; Does it have any [[White Whale]]s? | ; Does it have any [[White Whale]]s? | ||
| − | * [[ | + | * [[DrussGT]]? |
; What other robot(s) is it based on? | ; What other robot(s) is it based on? | ||
| − | Much of the code is shared with [[Leon]] and [[ | + | Much of the code is shared with [[Leon]], [[Gaff]] and [[Holden]], they all use the same code base. |
Revision as of 17:53, 27 August 2009
| Pris | |
| Author(s) | Darkcanuck |
| Extends | AdvancedRobot |
| Targeting | Neural Targeting (GF) |
| Movement | Neural Surfing |
| Released | June 2009 |
| Current Rating | 74th (72.4 APS) |
| Current Version | 0.84 (dev) |
| Code License | closed |
| Download | |
Sub-Pages: Version History | Challenges
Background Information
- What's special about it?
Pris is my return to learning bots, after some success and many struggles with Leon, a melee bot. By focusing on 1-on-1, Pris has the advantage of learning in a simpler environment. But the monsters at the top of the rankings should make learning challenging.
- How competitive is it?
In the top-100 of the 1-on-1 RoboRumble. I normally wait until version 1.0 before releasing, but this development version (0.20) was scoring as strong as Gaff on my benchmarks, even stronger in some areas. So I couldn't wait. :)
Strategy
- How does it move?
The latest version implements Wave Surfing with a neural network to store danger values. It appears to provide fast learning, while giving "standard" targeting methods a tough target to hit. There is still lots of room for improvement here, I've barely scratched the surface on this new strategy.
- How does it fire?
Uses Gaff's targeting, a combination of two neural networks which attempt to predict the most likely Guess Factor to aim at on any given turn.
- How does the melee strategy differ from One-on-one strategy?
No difference, but the movement algorithm doesn't take more than one opponent into account so melee performance could be pretty bad.
- How does it select a target to attack/avoid in melee?
Selects the closest target, with some protection against target thrashing.
- What does it save between rounds and matches?
Between rounds, saves all neural network weights and targeting stats.
Additional Information
- Where did you get the name?
Blade Runner. But this version does not do gymnastics.
- Can I use your code?
Not yet. But feel free to ask if you're curious and maybe I'll post some snippets.
- What's next for your robot?
- Bullet power selection is an area that needs more research, so I'd like to look into using Reinforcement Learning to generate a heuristic for selecting the right power.
- It would seem appropriate for Pris to have a ramming mode (minus cartwheels)?
- Does it have any White Whales?
- What other robot(s) is it based on?
Much of the code is shared with Leon, Gaff and Holden, they all use the same code base.
Credits
Pris uses the same targeting as Gaff which credits wcsv, Simonton, Rednaxela and Skilgannon to name a few, for inspiration, planting the seeds of new ideas and a few wee code snippets.
