Carsten H. Botts | Searcharxiv

arXiv2024

Bayesian Statistics: A Review and a Reminder for the Practicing Reliability Engineer

This paper introduces and reviews some of the principles and methods used in Bayesian reliability. It specifically discusses methods used in the analysis of success/no-success data and then reminds the reader of a simple Monte Carlo algorithm that can be used to calculate the posterior distribution of a system's reliability. This algorithm is especially useful when a system's reliability is modeled through the reliability of its subcomponents, yet only system-level data is available.

stat.ME↗

arXiv2021

Three-Dimensional Swarming Using Cyclic Stochastic Optimization

In this paper we simulate an ensemble of cooperating, mobile sensing agents that implement the cyclic stochastic optimization (CSO) algorithm in an attempt to survey and track multiple targets. In the CSO algorithm proposed, each agent uses its sensed measurements, its shared information, and its predictions of others' future motion to decide on its next action. This decision is selected to minimize a loss function that decreases as the uncertainty in the targets' state estimates decreases. Only noisy measurements of this loss function are available to each agent, and in this study, each agent attempts to minimize this function by calculating its stochastic gradient. This paper examines, via simulation-based experiments, the implications and applicability of CSO convergence in three dimensions.

stat.ML↗