Performance comparison of routing protocols using MaRS: distance-vector versus link-state
Performance comparison of routing protocols using MaRS: distance-vector versus link-state
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computer Networks
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Genetic Algorithm for Shortest Path Motion Problem in Three Dimensions
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
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AntNet is a new algorithm for packet routing in communication networks. In AntNet, a group of mobile agents (artificial ants) build paths between pair of nodes, exploring the network concurrently and exchanging data to update routing tables.This work, based in a previous work of the author [3], analyzes AntNet algorithms and proposes improvements, comparing their performance with respect to the original AntNet and other commercial algorithms. Simulation results indicate a better throughput of the improved proposals. So, AntNet and its variant here proposed are promising options for routing in large public networks such as Intemet.