Inverting Conditional Opinions in Subjective Logic

Subjective Logic has operators for conditional deduction and conditional abduction where subjective opinions are input arguments. With these operators traditional Bayesian reasoning can be generalised from taking only probabilistic arguments to also taking opinions as arguments, thereby allowing Bayesian modeling of situations affected by uncertainty and incomplete information. Conditional deduction is a Bayesian reasoning process that goes in the same direction as that of the input argument conditionals, whereas conditional abduction is a Bayesian reasoning process that goes in the direction opposite to that of the input argument conditionals. Conditional abduction is in fact a two-step process that first involves the computation of inverted conditionals, and then conditional deduction based on the inverted conditionals. This paper describes an improved generalized method for inverting opinion conditionals in order to support general Bayesian reasoning in subjective logic.