The branching-time temporal logic PCTL* has been introduced to specify quantitative properties over probability systems, such as discrete-time Markov chains. Until now, however, no logics have been defined to specify properties over hidden Markov models (HMMs). In HMMs the states are hidden, and the hidden processes produce a sequence of observations. In this paper we extend the logic PCTL* to POCTL*. With our logic one can state properties such as "there is at least a 90 percent probability that the model produces a given sequence of observations" over HMMs. Subsequently, we give model checking algorithms for POCTL* over HMMs
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
AbstractWe introduce p-Automata, which are automata that accept languages of Markov chains, by adapt...
It is crucial for accurate model checking that the model be a complete and faithful representation o...
The branching-time temporal logic PCTL* has been introduced to specify quantitative properties over ...
Abstract. The branching-time temporal logic PCTL ¤ has been intro-duced to specify quantitative prop...
The branching-time temporal logic PCTL* has been introduced to specify quantitative properties over ...
We present Hintikka games for formulae of the proba-bilistic temporal logic PCTL and countable label...
Model checking linear-time properties expressed in first-order logic has non-elementary complexity, ...
Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and depe...
Abstract We present algorithms for the qualitative and quantita-tive model checking of Linear Tempor...
Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and depe...
Model checking of Markov chains using logics like CSL or asCSL proves whether a logical formula hold...
We consider the model-checking problem of continuous-time Markov chains (CTMCs) with respect to Cond...
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
AbstractWe introduce p-Automata, which are automata that accept languages of Markov chains, by adapt...
It is crucial for accurate model checking that the model be a complete and faithful representation o...
The branching-time temporal logic PCTL* has been introduced to specify quantitative properties over ...
Abstract. The branching-time temporal logic PCTL ¤ has been intro-duced to specify quantitative prop...
The branching-time temporal logic PCTL* has been introduced to specify quantitative properties over ...
We present Hintikka games for formulae of the proba-bilistic temporal logic PCTL and countable label...
Model checking linear-time properties expressed in first-order logic has non-elementary complexity, ...
Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and depe...
Abstract We present algorithms for the qualitative and quantita-tive model checking of Linear Tempor...
Continuous-time Markov chains (CTMCs) have been widely used to determine system performance and depe...
Model checking of Markov chains using logics like CSL or asCSL proves whether a logical formula hold...
We consider the model-checking problem of continuous-time Markov chains (CTMCs) with respect to Cond...
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
In this paper we present an explicit verification algorithm for Probabilistic Systems defining discr...
AbstractWe introduce p-Automata, which are automata that accept languages of Markov chains, by adapt...
It is crucial for accurate model checking that the model be a complete and faithful representation o...