Martin, Andrew O.; Bishop, Mark (J. M.); Robinson, E.J.H. and Myatt, D.R.. 2018. Local termination criteria for Swarm Intelligence: a comparison between local Stochastic Diffusion Search and ant nest-site selection. In: Ngoc Thanh Nguyen; Richard Kowalczyk and Marcin Hernes, eds. Transactions on Computational Collective Intelligence XXXII. 11370 Berlin: Springer, pp. 140-167. ISBN 9783662586105 [Book Section]

Preview

Text Post_review.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial. Download (774kB) | Preview

Abstract or Description

Stochastic diffusion search (SDS) is a global Swarm Intelligence optimisation technique based on the behaviour of ants, rooted in the partial evaluation of an objective function and direct communication between agents. Although population based decision mechanisms employed by many Swarm Intelligence methods can suffer poor convergence resulting in ill-defined halting criteria and loss of the best solution, as a result of its resource allocation mechanism, the solutions found by Stochastic Diffusion Search enjoy excellent stability.
Previous implementations of SDS have deployed stopping criteria derived from global properties of the agent population; this paper examines new local SDS halting criteria and compares their performance with ‘quorum sensing’ (a termination criterion naturally deployed by some species of tandem-running ants). In this chapter we discuss two experiments investigating the robustness and efficiency of the new local termination criteria; our results demonstrate these to be (a) effectively as robust as the classical SDS termination criteria and (b) almost three times faster.

Item Type:	Book Section
Keywords:	Collective Decision Making, Ant Nest Selection, Stochastic Diffusion Search, Swarm Intelligence. Global Search
Departments, Centres and Research Units:	Computing > Embodied AudioVisual Interaction Group (EAVI)
Dates:	Date Event November 2018 Accepted 19 December 2018 Published
Item ID:	27335
Date Deposited:	30 Oct 2019 10:35
Last Modified:	09 Jun 2021 13:10
URI:	https://research.gold.ac.uk/id/eprint/27335

View statistics for this item...

Edit Record (login required)