Mathematics of Data Fusion
A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Trust network analysis with subjective logic
ACSC '06 Proceedings of the 29th Australasian Computer Science Conference - Volume 48
A method for access authorisation through delegation networks
ACSW Frontiers '06 Proceedings of the 2006 Australasian workshops on Grid computing and e-research - Volume 54
Simplification and analysis of transitive trust networks
Web Intelligence and Agent Systems
Probabilistic logic under uncertainty
CATS '07 Proceedings of the thirteenth Australasian symposium on Theory of computing - Volume 65
Subjective logic and arguing with evidence
Artificial Intelligence
Expert Assessment of Arguments: A Method and Its Experimental Evaluation
SAFECOMP '08 Proceedings of the 27th international conference on Computer Safety, Reliability, and Security
Exploring different types of trust propagation
iTrust'06 Proceedings of the 4th international conference on Trust Management
An empirical evaluation of geometric subjective logic operators
AT'13 Proceedings of the Second international conference on Agreement Technologies
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Conditional deduction in binary logic basically consists of deriving new statements from an existing set of statements and conditional rules. Modus Ponens, which is the classical example of a conditional deduction rule, expresses a conditional relationship between an antecedent and a consequent. A generalisation of Modus Ponens to probabilities in the form of probabilistic conditional inference is also well known. This paper describes a method for conditional deduction with beliefs which is a generalisation of probabilistic conditional inference and Modus Ponens. Meaningful conditional deduction requires a degree of relevance between the antecedent and the consequent, and this relevance can be explicitly expressed and measured with our method. Our belief representation has the advantage that it is possible to represent partial ignorance regarding the truth of statements, and is therefore suitable to model typical real life situations. Conditional deduction with beliefs thereby allows partial ignorance to be included in the analysis and deduction of statements and hypothesis.