Encoding Uncertain OR and MAX connectors for Weighted Model Counting in possibility theory

Uncertain logic gates facilitate the representation of knowledge in possibilistic networks. As the number of parents of a variable increases, the number of parameters to elicit becomes too large. Uncertain logic gates allow for the modeling of logical behaviors to combine binary variables using operators such as OR, AND, NOT, etc., and also generalize these connectors to the case of nonbinary variables. Other connectors can also be used. In this research, we will focus on the calculation of the parameters for two connectors : the uncertain OR and the uncertain MAX. These connectors can be encoded using clauses in conjunctive normal form, and their evaluation can be performed using weighted model counting. We will compare several solutions for encoding the uncertain OR and uncertain MAX connectors.