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Incorporating Swarm Intelligence Into Computer AI
An anonymous reader writes "From optimizing truck delivery routes to inspiring nerve-cell-based cognition models, ant intelligence has arrived. From the Economist: 'In 1992 Dr. Dorigo and his group began developing Ant Colony Optimisation (ACO), an algorithm that looks for solutions to a problem by simulating a group of ants wandering over an area and laying down pheromones. ACO proved good at solving travelling-salesman-type problems. Since then it has grown into a whole family of algorithms, which have been applied to many practical questions. ... Ant-like algorithms have also been applied to the problem of routing information through communication networks. Dr. Dorigo and Gianni Di Caro, another researcher at IDSIA, have developed AntNet, a routing protocol in which packets of information hop from node to node, leaving a trace that signals the "quality" of their trip as they do so. Other packets sniff the trails thus created and choose accordingly. In computer simulations and tests on small-scale networks, AntNet has been shown to outperform existing routing protocols."
It just sounds like the classic hill climbing algorithm to me.
That's because it's very similar -- with a massive stochastic component. It might be effective at routing, but I image leaving "pheromone traces" over network routes to indicate quality (latency, bandwidth, whatever) is something that will make sure security researchers have jobs for a long, long time.
An old-timer with old-timey ideas.
I'm not sure I understand your post.
UDP packet order is already unreliable. You have to build in your own sequencing and error-correction logic at the application level (if you need it).
Again, UDP does not fit this description. Are you sure you're not confusing TCP and UDP?
http://en.wikipedia.org/wiki/User_Datagram_Protocol#Comparison_of_UDP_and_TCP
"Mind, as manifested by the capacity to make choices, is to some extent present in every electron." -Freeman Dyson