Adaptive Group Testing Algorithms to Estimate the Number of Defectives

TL;DR

This paper introduces an improved adaptive group testing algorithm for estimating the number of defectives with fewer tests, establishing its optimality through theoretical bounds.

Contribution

It presents a new adaptive testing algorithm that minimizes the number of queries needed to estimate defectives and proves its optimality with a matching lower bound.

Findings

The algorithm reduces the number of tests compared to previous methods.

Theoretical proof of the algorithm's optimality for constant estimation.

Establishment of a lower bound confirming the algorithm's efficiency.

Abstract

We study the problem of estimating the number of defective items in adaptive Group testing by using a minimum number of queries. We improve the existing algorithm and prove a lower bound that show that, for constant estimation, the number of tests in our algorithm is optimal.