Recent work on loglinear models in probabilistic constraint logic programming is applied to firstorder probabilistic reasoning. Probabilities are defined directly on the proofs of atomic formulae, and by marginalisation on the atomic formulae themselves. We use Stochastic Logic Programs (SLPs) composed of labelled and unlabelled definite clauses to define the proof probabilities. We have a cons...

the current study investigated and compared data generation methods for groundwater modeling. thesemethods can be divided into two classes; geostatistic and probabilistic. by comparing geostatistic methods,the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study area ina grid (9-cell) format. after observing weak spatial correlation between the data, th...

We introduce probabilistic many-valued logic programs in which the implication connective is interpreted as material implication. We show that probabilistic many-valued logic programming is computationally more complex than classical logic programming. More precisely, some deduction problems that are P-complete for classical logic programs are shown to be co-NP-complete for probabilistic many-v...

For a given target system and apparatus described by quantum theory, the so-called no-programming theorem indicates that family of states called programs in with fixed unitary operation on total distinct dynamics to only if initial are orthogonal each other. The current study aims at revealing whether similar behavior can be observed generalized probabilistic theories (GPTs). Generalizing progr...

In [23], a new Hybrid Probabilistic Logic Programs framework has been proposed, and a new semantics has been developed to enable encoding and reasoning about real-world applications. In this paper, the language of Hybrid Probabilistic Logic Programs framework of [23] is extended to allow non-monotonic negation, and two alternative semantics are defined: stable probabilistic model semantics and ...

Real-time model-based eduction has recently emerged as a vital component in Al’s tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods imultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification o...