Inferences in probability logic

In this paper, we present a logic $\mathbf{FPL}$ (Frequentist Probability Logic) to reason about probabilities with a relative frequency interpretation. We show that it is possible to interpret the language of $\mathbf{FPL}$ with the standard semantics for ...$\mathbf{}$

As a classical probabilistic graphic model, Bayesian network (BN) is widely used for representing and inferring dependence relationships with uncertainties. However, multiple probabilistic inferences on BN are quite inefficient, since ...

• Construct the WDG to represent the states with transition probabilities in BN.
• ...

In real applications established on Bayesian networks (BNs), it is necessary to make inference for arbitrary evidence even it is not contained in existing conditional probability tables (CPTs). Aiming at this problem, in this paper, we discuss the ...