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This paper focuses on a linguistic-valued temporal logic based reasoning formalism for dynamically modelling and merging information under uncertainty in some real world systems where the state of a system evolves over time and the transition through states depends on uncertain conditions. We provide forward and backward reasoning algorithms which,(More)
Temporality and uncertainty are important features of real world systems where the state of a system evolves over time and the transition through states depends on uncertain conditions. Examples of such application areas where these concepts matter are smart home systems, disaster management, and robot control etc. Solving problems in such areas usually(More)
Decision-making on uncertain and dynamic domains is still a challenging research area. This paper explores a solution to handle such complex decision making based on a combined logic system. We provide an explanation of our reasoning system focused on the algorithms and their implementations. The reasoning system is based on a multi-valued temporal(More)
Temporality and uncertainty are important features of many real world systems. Solving problems in such systems requires the use of formal mechanism such as logic systems, statistical methods or other reasoning and decision-making methods. In this paper, we propose a linguistic truth-valued temporal reasoning formalism to enable the management of both(More)
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