### Abstract

We consider a distributed multi-agent network system where the goal is to minimize an objective function that can be written as the sum of component functions, each of which is known (with stochastic errors) to a specific network agent. We propose an asynchronous algorithm that is motivated by a random gossip scheme where each agent has a local Poisson clock. At each tick of its local clock, the agent averages its estimate with a randomly chosen neighbor and adjusts the average using the gradient of its local function that is computed with stochastic errors. We investigate the convergence properties of the algorithm for two different classes of functions: differentiable but not necessarily convex and convex but not necessarily differentiable.

Original language | English (US) |
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Title of host publication | Proceedings of the 2009 International Conference on Game Theory for Networks, GameNets '09 |

Pages | 80-81 |

Number of pages | 2 |

DOIs | |

State | Published - Oct 20 2009 |

Externally published | Yes |

Event | 2009 International Conference on Game Theory for Networks, GameNets '09 - Istanbul, Turkey Duration: May 13 2009 → May 15 2009 |

### Publication series

Name | Proceedings of the 2009 International Conference on Game Theory for Networks, GameNets '09 |
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### Other

Other | 2009 International Conference on Game Theory for Networks, GameNets '09 |
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Country | Turkey |

City | Istanbul |

Period | 5/13/09 → 5/15/09 |

### ASJC Scopus subject areas

- Computer Networks and Communications
- Computer Vision and Pattern Recognition

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## Cite this

*Proceedings of the 2009 International Conference on Game Theory for Networks, GameNets '09*(pp. 80-81). [5137386] (Proceedings of the 2009 International Conference on Game Theory for Networks, GameNets '09). https://doi.org/10.1109/GAMENETS.2009.5137386