Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Ant-based load balancing in telecommunications networks
Adaptive Behavior
Ant algorithms for discrete optimization
Artificial Life
Cross-entropy and rare events for maximal cut and partition problems
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue: Rare event simulation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Using the Cross-Entropy Method to Guide/Govern Mobile Agent's Path Finding in Networks
MATA '01 Proceedings of the Third International Workshop on Mobile Agents for Telecommunication Applications
Packet Routing with Genetically Programmed Mobile Agents
SMARTNET '00 Proceedings of the IFIP TC6 WG6.7 Sixth International Conference on Intelligence in Networks: Telecommunication Network Intelligence
Exact and Approximate Nondeterministic Tree-Search Procedures for the Quadratic Assignment Problem
INFORMS Journal on Computing
Cross entropy guided ant-like agents finding dependable primary/backup path patterns in networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
IEEE Communications Magazine
Mobile software agents: an overview
IEEE Communications Magazine
A novel fault-tolerant execution model by using of mobile agents
Journal of Network and Computer Applications
A stochastic clustering algorithm for swarm compact routing
NGI'09 Proceedings of the 5th Euro-NGI conference on Next Generation Internet networks
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Finding paths in networks is a well exercised activity both in theory and practice but still remains a challenge when the search domain is a dynamic communication network environment with changing traffic patterns and network topology. To enforce dependability in such network environments new routing techniques are called upon. In this paper we describe a distributed algorithm capable of finding cyclic paths in scarcely meshed networks using ant-like agents. Cyclic paths are especially interesting in the context of protection switching, and scarce meshing is typical in real world telecommunication networks. Two new next-node-selection strategies for the ant-like agents are introduced to better handle low degrees of meshing. Performance results from Monte Carlo Simulations of systems implementing the strategies are presented indicating a promising behavior of the second strategy.