Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The BDI architecture, where agents are modelled based on their beliefs, desires and intentions, provides a practical approach to develop large scale systems. Hover, it is not ll suited to model complex Supervisory Control And Data Acquisition (SCADA) systems pervaded by uncertainty.   address this issue by extending the operational semantics of CAN(PLAN) into CAN(PLAN)+.  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  identify fragments with computationally efficient semantics. Finally,  examine how primitive actions are affected by uncertainty and  define an appropriate form of lookahead planning.
['Kim Bauters', 'Weiru Liu', 'Jun Hong', 'Carles Sierra', 'Lluís Godo']
I am writing a research paper on a idea CAN(PLAN)+: extending the operational semantics of the BDI architecture to deal with uncertain information
[{"from": "human", "value": "I am writing a research paper on a idea CAN(PLAN)+: extending the operational semantics of the BDI architecture to deal with uncertain information"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The BDI architecture, where agents are modelled based on their beliefs, desires and intentions, provides a practical approach to develop large scale systems. Hover, it is not ll suited to model complex Supervisory Control And Data Acquisition (SCADA) systems pervaded by uncertainty.   address this issue by extending the operational semantics of CAN(PLAN) into CAN(PLAN)+.  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  identify fragments with computationally efficient semantics. Finally,  examine how primitive actions are affected by uncertainty and  define an appropriate form of lookahead planning."}]