Publications

@inproceedings{HSCC20Jarne,

title = {Convergence of Ant Colony Multi-Agent Swarms},

author = { Daniel Jarne Ornia and Manuel {Mazo Jr.}},

url = {https://mmazojr.3me.tudelft.nl/wp-content/uploads/2020/09/HSCC_Jarne_Mazo.pdf

https://dl.acm.org/doi/10.1145/3365365.3382199

},

doi = {10.1145/3365365.3382199},

isbn = {9781450370189},

year  = {2020},

date = {2020-04-01},

booktitle = {Proceedings of the 23rd International Conference on Hybrid Systems: Computation and Control},

number = {29},

publisher = {Association for Computing Machinery},

address = {Sydney, New South Wales, Australia},

series = {HSCC '20},

abstract = {Ant Colony algorithms are a set of biologically inspired algorithms used commonly to solve distributed optimization problems. Convergence has been proven in the context of optimization processes, but these proofs are not applicable in the framework of robotic control. In order to use Ant Colony algorithms to control robotic swarms, we present in this work more general results that prove asymptotic convergence of a multi-agent Ant Colony swarm moving in a weighted graph.},

keywords = {Robotics, SCARS},

pubstate = {published},

tppubtype = {inproceedings}

}