The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Emergent colonization and graph partitioning
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
An improved spectral graph partitioning algorithm for mapping parallel computations
SIAM Journal on Scientific Computing
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
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In this article partitioning of finite element meshes is tackled using colonies of artificial ant-like agents. These agents must restructure the resources in their environment in a manner which corresponds to a good solution of the underlying problem. Standard approaches to these problems use recursive methods in which the final solution is dependent on solutions found at higher levels. For example partitioning into k sets is done using recursive bisection which can often provide a partition which is far from optimal [15]. The inherently parallel, distributed nature of the swarm-based paradigm allows us to simultaneously partition into k sets. Results show that this approach can be superior in quality when compared to standard methods. Whilst it is marginally slower, the reduced communication cost will greatly reduce the much longer simulation phase of the finite element method. Hence this will outweigh the initial cost of making the partition.