Hybrid and Reinforcement Multi Agent Technology for Real Time Air Pollution Monitoring - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Hybrid and Reinforcement Multi Agent Technology for Real Time Air Pollution Monitoring

Résumé

This paper describes the design and implementation of a modular hybrid intelligent model and system, for monitoring and forecasting of air pollution in major urban centers. It is based on Multiagent technologies, Artificial Neural Networks (ANN), Fuzzy Rule Based sub-systems and it uses a Reinforcement learning approach. A multi level architecture with a high number of agent types was employed. Multiagent’s System modular and distributed nature, allows it’s interconnection with existing systems and it reduces its functional cost, allowing its extension by incorporating decision functions and real time imposing actions capabilities.
Fichier principal
Vignette du fichier
978-3-642-33409-2_29_Chapter.pdf (200.74 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01521429 , version 1 (11-05-2017)

Licence

Paternité

Identifiants

Citer

Andonis Papaleonidas, Lazaros Iliadis. Hybrid and Reinforcement Multi Agent Technology for Real Time Air Pollution Monitoring. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.274-284, ⟨10.1007/978-3-642-33409-2_29⟩. ⟨hal-01521429⟩
93 Consultations
94 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More