Abstract
In earlier work of the authors simulation results indicated the possibility of achieving self-organization of autonomous vehicles through Gibbs sampler-based simulated annealing. However, the dynamic graph structure associated with the network evolution presents challenges in convergence analysis. In this paper a novel algorithm is presented and shown to yield desired global configurations with primarily local interactions. Its convergence speed is provided in terms of the Gibbs potential function. The analytical results are further verified through simulation.
Keywords
Convergence (economics)Computer scienceSimulated annealingAlgorithmGraphMathematical optimizationTheoretical computer scienceMathematics
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Publication Info
- Year
- 2006
- Type
- article
- Volume
- 6
- Pages
- 765-770
- Citations
- 19
- Access
- Closed
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Cite This
Xi Wei,
Xiaobo Tan,
John S. Baras
(2006).
A Stochastic Algorithm for Self-Organization of Autonomous Swarms.
, 6
, 765-770.
https://doi.org/10.1109/cdc.2005.1582249
Identifiers
- DOI
- 10.1109/cdc.2005.1582249