Ola.
Well, my A* algorithm is already working very nicely - and imo there
isn't any problem-specific optimization left to implement other than the
data structures holding the nodes themselves. So the question is only
whether it would pay off to switch to D* instead.
Second, I'm aiming for the #1 spot :D. I have a lot of strategy in mind
that I haven't seen implemented by anyone else yet and I think a TOP 10
spot should definitely be possible. Minimizing the impact of the
path-finding on computing requirements is thus certainly a priority.
/Max
On 10/29/2011 9:26 PM, Lishaak Bystroushaak wrote:
Hi.
I don't think, that you have to use some advanced strategies and path
finding. I'm currently 261 with this simple code:
http://pastebin.com/1Nsb81rj With hill defense and ant grouping, you
could be imho easilly in first 100 without A* :)
2011/10/29 Sean Kelly<[email protected]>:
If you want to cheat, there have been books published on ant colony
optimization. I'm sure the related papers could be dug up.
Sent from my iPhone
On Oct 29, 2011, at 3:12 AM, Max Wolter<[email protected]> wrote:
On 10/25/2011 1:44 PM, Trass3r wrote:
I'm working on a bot in D. I'm currently done implementing the A*
algorithm for path finding
Dump A*, D* Lite ftw ;)
Hellooo.
Correct me if I'm wrong, but in A*, I can just find a path, store it (let's say
as a string) and find a new one if it's blocked for some reason.
As far as I could see from what I've read about Lifelong A*, D*, Focused D* and
D* Lite, I would have to store all nodes used in the algorithm - so, as opposed
to A*, I have to conserve the state of the entire search algorithm throughout
ticks, for each ant.
Is the environment in this AI challenge really noisy enough to warrant this?
Obviously, if the path needs to be re-planned almost every tick, D* Lite seems
like a better choice to me. But if you have 100+ ants, that would be a lot of
allocated heap memory, wouldn't it?
I really don't have a clue how the processing vs allocating should be weighed
here performance-wise.
/Max
