Abstract
In this paper, we present a distributed algorithm to solve unconstrained distributed Least Squares optimization problems over networks where the communication links could stochastically break. The iterative algorithm allows each node with limited computation and communication capabilities to obtain the optimal solution of the centralized problem. We provide the convergence analysis of the algorithm based on an internal structure decomposition and an application of stochastic systems theory. The results suggests that agents with simple dynamics, one step memory and local gradient information could collectively solve complicated optimization problems in the presence of unreliable communications.
| Original language | English (US) |
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| Title of host publication | 2012 American Control Conference, ACC 2012 |
| Pages | 6479-6484 |
| Number of pages | 6 |
| State | Published - Nov 26 2012 |
| Externally published | Yes |
| Event | 2012 American Control Conference, ACC 2012 - Montreal, QC, Canada Duration: Jun 27 2012 → Jun 29 2012 |
Other
| Other | 2012 American Control Conference, ACC 2012 |
|---|---|
| Country/Territory | Canada |
| City | Montreal, QC |
| Period | 6/27/12 → 6/29/12 |