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CAN (PLAN)+: Extending the operational semantics of the BDI architecture to deal with uncertain information

Bauters, Kim; Liu, Weiru; Hong, Jun; Sierra, Carles; Godo, Lluis


Kim Bauters

Weiru Liu

Jun Hong
Professor in Artificial Intelligence

Carles Sierra

Lluis Godo


The BDI architecture, where agents are modelled based on their beliefs, desires and intentions, provides a practical approach to develop large scale systems. However, it is not well suited to model complex Supervisory Control And Data Acquisition (SCADA) systems pervaded by uncertainty. In this paper we address this issue by extending the operational semantics of CAN(PLAN) into CAN(PLAN)+. We start by modelling the beliefs of an agent as a set of epistemic states where each state, possibly using a different representation, models part of the agent’s beliefs. These epistemic states are stratified to make them commensurable
and to reason about the uncertain beliefs of the agent. The syntax and semantics of a BDI agent are extended accordingly and we identify fragments with computationally efficient semantics. Finally, we examine how primitive actions
are affected by uncertainty and we define an appropriate form of lookahead planning.


Bauters, K., Liu, W., Hong, J., Sierra, C., & Godo, L. (2014, July). CAN (PLAN)+: Extending the operational semantics of the BDI architecture to deal with uncertain information. Paper presented at UAI, Quebec, Canada

Presentation Conference Type Conference Paper (unpublished)
Conference Name UAI
Conference Location Quebec, Canada
Start Date Jul 23, 2014
End Date Jul 27, 2014
Acceptance Date Jul 23, 2014
Publication Date Jul 23, 2014
Deposit Date Feb 14, 2017
Peer Reviewed Peer Reviewed
Pages 52-61
Keywords CAN, PLAN, extending, operational, semantics, BDI, architecture, uncertain, information
Public URL
Publisher URL
Additional Information Title of Conference or Conference Proceedings : The 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014)