TY - GEN
T1 - Incorporating PGMs into a BDI architecture
AU - Chen, Yingke
AU - Hong, Jun
AU - Liu, Weiru
AU - Godo, Lluís
AU - Sierra, Carles
AU - Loughlin, Michael
PY - 2013
Y1 - 2013
N2 - In 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.
AB - In 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.
UR - http://www.scopus.com/inward/record.url?scp=84893060965&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-44927-7_5
DO - 10.1007/978-3-642-44927-7_5
M3 - Conference contribution
AN - SCOPUS:84893060965
SN - 9783642449260
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 54
EP - 69
BT - PRIMA 2013
T2 - 16th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2013
Y2 - 1 December 2013 through 6 December 2013
ER -