Revisiting the Auto-Regressive Functions of the Cross-Entropy Ant System

Authors:
Laurent Paquereau;Bjarne E. Helvik
Affiliations:
Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology, Trondheim, Norway;Centre for Quantifiable Quality of Service in Communication Systems, Norwegian University of Science and Technology, Trondheim, Norway
Venue:
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Year:
2009

Citing 4
Cited 0

Swarm intelligence: from natural to artificial systems

Swarm intelligence: from natural to artificial systems
Ant algorithms for discrete optimization

Artificial Life
Using the Cross-Entropy Method to Guide/Govern Mobile Agent's Path Finding in Networks

MATA '01 Proceedings of the Third International Workshop on Mobile Agents for Telecommunication Applications
Overhead reduction in a distributed path management system

Computer Networks: The International Journal of Computer and Telecommunications Networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Cross-Entropy Ant System (CEAS) is an Ant Colony Optimization (ACO) system for distributed and online path management in telecommunication networks. Previous works on CEAS have enhanced the system by introducing new features. This paper takes a step back and revisits the auto-regressive functions at the core of the system. These functions are approximations of complicated transcendental functions stemming from the Cross-Entropy (CE) method for stochastic optimization, computationally intensive and therefore not suited for online and distributed operation. Using linear instead of hyperbolic approximations, new expressions are derived and shown to improve the adaptivity and robustness of the system, in particular on the occurrence of radical changes in the cost of the paths sampled by ants.