e-ISSN: Pending
Failed Experiment ReportOpen accessComputer Science

Evaluation and Improvement of Laruelle-Widgrén Inverse Banzhaf Approximation

Frits de Nijs; Daan Wilmer · 2012 · arXiv

WASTE classifies this as Failed Experiment Report · AI classification, approximate

An experimental approach did not work as intended — learn what to avoid before investing the same effort.

Abstract (excerpt)

The goal of this paper is to critically evaluate a heuristic algorithm for the Inverse Banzhaf Index problem by Laruelle and Widgrén. Few qualitative results are known about the approximation quality of the heuristics for this problem. The intuition behind the operation of this approximation algorithm is analysed and evaluated. We found that the algorithm can not handle general inputs well, and often fails to improve inputs. It is also shown to diverge after only tens of iterations. We present three alternative extensions of the algorithm that do not alter the complexity but can result in up t

Excerpt shown for reference under fair use — read the full paper at the publisher.

About to run something similar?

Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.

WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.

Metadata source: arXiv