| Literature DB >> 12171633 |
Nicolas Meuleau1, Marco Dorigo.
Abstract
In this article, we study the relationship between the two techniques known as ant colony optimization (ACO) and stochastic gradient descent. More precisely, we show that some empirical ACO algorithms approximate stochastic gradient descent in the space of pheromones, and we propose an implementation of stochastic gradient descent that belongs to the family of ACO algorithms. We then use this insight to explore the mutual contributions of the two techniques.Entities:
Mesh:
Year: 2002 PMID: 12171633 DOI: 10.1162/106454602320184202
Source DB: PubMed Journal: Artif Life ISSN: 1064-5462 Impact factor: 0.667