Ants good at solving complex maths, page 2
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reply posted on 21-12-2010 @ 09:45 AM by peck420
reply to post by peacevic



I was refering more to the fact that water will move via all possible paths at the beginning, but will gradually move to follow the shortest possible path that it can take. Yes it is governed by gravity, but the principal is the same. It essentially floods all available pathways, and takes the one of least resistance. Same as ants.


reply posted on 21-12-2010 @ 09:58 AM by peacevic
reply to post by peck420



I understand what you are saying, but I think it's different than the ants. They didn't flood all possible pathways and then take the one of least resistance. And what water does when a path is blocked is different.

Read the article if you haven't already. I understand if you don't think it's up to par with human engineering (and I agree), but what they did is still pretty interesting, as is the fact that we can apply what the ants did to improve network management algorithms.


reply posted on 21-12-2010 @ 03:58 PM by peck420
reply to post by peacevic



I have read the article.

They make no mention of the method the ants use or how large the maze is or even of the number of ants.

The only reference they make is time (1hr intervals) and total number of pathways (32,768).

Here is a better article on this experiment: Article

They at least state some hard numbers, although it is still lacking information.

It even describes how the ants aren't thinking at all, and that nature has built this optimization directly into their pheremone system.

Quote:
"Ants establish optimal routes by leaving behind trails of pheromones that are attractive to other ants.

Because the pheromones evaporate over time, shorter, more well-travelled trails become increasingly attractive.

Reid speculated that ants and their pheromones could be modelled by data packets that left behind a line of code that expired after a set period of time.

Different lines of code with different "evaporation rates" could be used to model trail pheromones, and the exploration pheromones that were likely laid during the pre-exposure period, he said.

He expected more flexible, nature-inspired algorithms to improve logistical programs to maximise efficiency of industrial processes."

I don't know where the idea that "ants good at solving complex maths" comes from, in regards to the article sourced by the OP.

After reading the scientists own words, it seems more like they found a better way to model information flow based on the same principles as ant movement.

Edit to add: Didn't realize that I was just reitterating your thoughts with my last sentence, seems we agree on the end results .
edit on 21-12-2010 by peck420 because: (no reason given)



reply posted on 21-12-2010 @ 04:14 PM by peacevic
reply to post by peck420



Yes - that's what I meant. We can learn alot from nature! And in places we don't suspect.
Thanks for the article - it did have more information in it.
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