From a computational perspective, there is a close connection between various probabilistic reasoning tasks and the problem of counting or sampling satisfying assignments of a pro...
How to compute marginals efficiently is one of major concerned problems in probabilistic reasoning systems. Traditional graphical models do not preserve all conditional independen...
A new language and inference algorithm for stochastic modeling is presented. This work refines and generalizes the stochastic functional language originally proposed by [1]. The l...
We present a new approach for finding generalized contingent plans with loops and branches in situations where there is uncertainty in state properties and object quantities, but ...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
Markovian testing and trace equivalences have been recently proposed as reasonable alternatives to Markovian bisimilarity, as both of them induce at the Markov chain level an aggr...