An intelligent swarm of markovian agents

Dario Bruneo, Marco Scarpa, Andrea Bobbio, Davide Cerotti, Marco Gribaudo

Risultato della ricerca: Capitolo in libro/report/atti di convegnoContributo in volume (Capitolo o Saggio)peer review

Abstract

We define a Markovian agent model (MAM) as an analytical model formed by a spatial collection of interacting Markovian agents (MAs), whose properties and behavior can be evaluated by numerical techniques. MAMs have been introduced with the aim of providing a flexible and scalable framework for distributed systems of interacting objects, where both the local properties and the interactions may depend on the geographical position. MAMs can be proposed to model biologically inspired systems since they are suited to cope with the four common principles that govern swarm intelligence: positive feedback, negative feedback, randomness, and multiple interactions. In the present work, we report some results of a MAM for a wireless sensor network (WSN) routing protocol based on swarm intelligence, and some preliminary results in utilizing MAs for very basic ant colony optimization (ACO) benchmarks.

Lingua originaleInglese
Titolo della pubblicazione ospiteSpringer Handbook of Computational Intelligence
EditoreSpringer Berlin Heidelberg
Pagine1345-1359
Numero di pagine15
ISBN (elettronico)9783662435052
ISBN (stampa)9783662435045
DOI
Stato di pubblicazionePubblicato - 1 gen 2015
Pubblicato esternamente

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