Abstract. Temporal programming languages are recognized as natural and expressive formalisms for describing dynamic systems. However, most such languages are based on linear ow of ...
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
We describe a new approach to model construction using transfer function diagrams that are consequently mapped into generalized loopy logic, a first-order, Turing-complete stochas...
Nikita A. Sakhanenko, Roshan Rammohan, George F. L...
Abstract. Coordination languages are often used to describe open ended systems. This makes it challenging to develop tools for guaranteeing security of the coordinated systems and ...
Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fu...