Probabilistic models are useful for analyzing systems which operate under the presence of uncertainty. In this paper, we present a technique for verifying safety and liveness prop...
In this paper by considering an answer set programming approach and some basic ideas from possibilistic logic, we introduce a possibilistic disjunctive logic programming approach t...
Juan Carlos Nieves, Mauricio Osorio, Ulises Cort&e...
Switching model captures the data-driven uncertainty in logic circuits in a comprehensive probabilistic framework. Switching is a critical factor that influences dynamic, active ...
Current research in automatic subjectivity analysis deals with various kinds of subjective statements involving human attitudes and emotions. While all of them are related to subj...
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...