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CAN(PLAN)+: Extending the Operational Semantics of the BDI Architecture to deal with Uncertain Information

AuthorsBauters, Kim; Liu, Weiru; Hong, Jun; Sierra, Carles ; Godo, Lluis
KeywordsBDI architecture
Uncertain informations
Uncertain beliefs
Primitive actions
Operational semantics
Model complexes
Large scale systems
SCADA systems
Computationally efficient
Issue Date23-Jul-2014
PublisherAssociation for Uncertainty in Artificial Intelligence
CitationProceedings of the Thirtieth Conference Conference on Uncertainty in Artificial Intelligence ( 2014 ), July 23- 27 2014, Quebec City, Quebec, Canada, pp. 52-61
AbstractThe 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 look ahead planning.
Identifiersisbn: 978-0-9749039-1-0
Appears in Collections:(IIIA) Comunicaciones congresos
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