Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.550789
Title: Multi-valued temporal logic based reasoning system with applications to decision support in intelligent environments
Author: Lu, Zhirui
Awarding Body: University of Ulster
Current Institution: Ulster University
Date of Award: 2011
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Abstract:
This work deals with decision-making problems with uncertain information in dynamic environment. It develops a new logic system, multi-valued temporal propositional logic, combining multi-valued logic and linear temporal logic. This new logic allows uncertain information to be represented with either a numerical truth value in the [0,1] interval or a linguistic value, and uses these values with both states and same-time and next-time rules. Multi-valued temporal propositional logic, a generic logic system, provides a simple calculus for analysing uncertain information with Lukasiewicz implication algebra. It introduces uncertainty and temporality into rules. Soundness and completeness theorems provide a theoretical foundation for the reasoning system. Based on the new logic, forward and backward reasoning algorithms are proposed, which offers simulation/prediction and query answering functions. The reasoning system, based on the forward and backward reasoning algorithms was programmed in Pro log. Three scenarios were then used to evaluate this reasoning system. The results of the evaluations showed that the proposed reasoning system could return reliable and reasonable feedback to users on their input. Furthermore, users are able to perfect their knowledge bases according to the feedback from the reasoning system on their input. A general comparison between the reasoning system and dynamic Bayesian networks with a simple scenario with uncertain information in a certain temporal environment was undertaken. Within this comparison, an analysis of advantages and disadvantages between the proposed reasoning system and dynamic ~ Bayesian networks has been provided.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.550789  DOI: Not available
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