Distributed probabilistic bisection search using social learning
- Resource Type
- Conference
- Authors
- Tsiligkaridis, Athanasios; Tsiligkaridis, Theodoros
- Source
- 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on. :4069-4073 Mar, 2017
- Subject
- Signal Processing and Analysis
Collaboration
Convergence
Probabilistic logic
Error probability
Noise measurement
Signal processing algorithms
Algorithm design and analysis
Probabilistic bisection
consensus
decentralized estimation
convergence rate
belief sharing
- Language
- ISSN
- 2379-190X
We present a novel distributed probabilistic bisection algorithm using social learning with application to target localization. Each agent in the network first constructs a query about the target based on its local information and obtains a noisy response. Agents then perform a Bayesian update of their beliefs followed by an averaging of the log beliefs over local neighborhoods. This two stage algorithm consisting of repeated querying and averaging runs until convergence. We derive bounds on the rate of convergence of the beliefs at the correct target location. Numerical simulations show that our method outperforms current state of the art methods.