AbstractGrammatical Evolution (GE) is one of the most popular Genetic Programming (GP) variants, and it has been used with success in several problem domains. Since original proposal, many enhancements have proposed to GE order address some its main issues improve performance.In this paper we propose Probabilistic Grammatical (PGE), which introduces a new genotypic representation mapping mechan...

We consider a class of cooperative network games with transferable utilities in which players interact through probabilistic rather than regular, deterministic network. In this wealth-generating situations we extensions the Myerson value and position value. For subclass multilinear form, establish characterizations these values using an appropriate formulation component balancedness. show axiom...

Probabilistic databases (PDBs) model uncertainty in data a quantitative way. In the established formal framework, probabilistic (relational) are finite probability spaces over relational database instances. This finiteness can clash with intuitive query behavior (Ceylan et al., KR 2016), and application scenarios that better modeled by continuous distributions (Dalvi CACM 2009). We formally int...

support vector regression (svr) solves regression problems based on the concept of support vector machine (svm). in this paper, a new model of svr with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...

In today’s uncertain world, imprecision in probabilistic information is often specified by probability intervals. We present here a new database framework for the efficient storage and manipulation of interval probability distribution functions and their associated contextual information. While work on interval probabilities and on probabilistic databases, has appeared before, ours is the first...