|Targeting||Neural Targeting (GF)|
|Current Rating||17th (85.23 APS)|
- 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. :)
- 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?
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.
- 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?