English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/133446
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:


Incorporating PGMs into a BDI Architecture

AuthorsChen, Yingke; Hong, Jun; Liu, Weiru; Godo, Lluis ; Sierra, Carles ; Loughlin, Michael
KeywordsStochastic environment
Influence diagram
Supervisory control and data acquisition
Transit scenarios
Uncertainty reasoning
Probabilistic graphical models
BDI (belief-desire-intention)
Decision making process
Issue Date1-Dec-2013
CitationLecture Notes in Computer Science 8291. PRIMA 2013: Principles and Practice of Multi-Agent Systems, 16th International Conference, Dunedin, New Zealand, December 1-6, 2013. Proceedings, pp. 54-69.
AbstractIn this paper, we present a hybrid BDI-PGM framework, in which PGMs (Probabilistic Graphical Models) are incorporated into a BDI (belief-desire-intention) architecture. This work is motivated by the need to address the scalability and noisy sensing issues in SCADA (Supervisory Control And Data Acquisition) systems. Our approach uses the incorporated PGMs to model the uncertainty reasoning and decision making processes of agents situated in a stochastic environment. In particular, we use Bayesian networks to reason about an agent's beliefs about the environment based on its sensory observations, and select optimal plans according to the utilities of actions defined in influence diagrams. This approach takes the advantage of the scalability of the BDI architecture and the uncertainty reasoning capability of PGMs. We present a prototype of the proposed approach using a transit scenario to validate its effectiveness. © 2013 Springer-Verlag.
Identifiersdoi: 10.1007/978-3-642-44927-7_5
isbn: 978-3-642-44926-0
Appears in Collections:(IIIA) Comunicaciones congresos
Files in This Item:
File Description SizeFormat 
LNCS8291_54-69.pdf660,54 kBUnknownView/Open
Show full item record
Review this work

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.