Abstract
Various metaheuristics have been successfully employed to address \(\mathcal{NP}\)-hard problems. Many strategies adopt techniques inspired from nature to efficiently find high-quality near-optimal solutions for complex real-world problems. In [47] is proposed a combination between Ant Colony Systems (ACS) and Multi-Agent Systems (MAS) to produce a more powerful method to efficiently address \(\mathcal{NP}\)-hard problems. The agents that form a system inter-operate to produce a solution using both direct and indirect (stigmergic) communication. In this way, intelligent problem solutions can naturally emerge due to stigmergy (see section 3.1).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Pintea, CM. (2014). Stigmergic Collaborative Agents. In: Advances in Bio-inspired Computing for Combinatorial Optimization Problems. Intelligent Systems Reference Library, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40179-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-40179-4_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40178-7
Online ISBN: 978-3-642-40179-4
eBook Packages: EngineeringEngineering (R0)