Compiling Bayesian networks (BNs) to junction trees and performing belief propagation over them is among the most prominent approaches to computing posteriors in BNs. However, bel...
Main stream approaches in distributed artificial intelligence (DAI) are essentially logic-based. Little has been reported to explore probabilistic approach in DAI. On the other han...
— We consider the problem of tracking multiple moving robots using noisy sensing of inter-robot and interbeacon distances. Sensing is local: there are three fixed beacons at kno...
Jeremy Schiff, Erik B. Sudderth, Kenneth Y. Goldbe...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
The estimation error performance of Gaussian belief propagation based distributed estimation in a large sensor network employing random sleep strategies is explicitly evaluated fo...