A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Regions which evolve over time are a significant aspect of many phenomena in geographic information science. Examples include areas in which a measured value (e.g. temperature, sal...
Matt Duckham, John G. Stell, Maria Vasardani, Mich...
The problem of "time separation" can be stated as follows: Given a system made of several connected components, each one entailing a local delay known with uncertainty, ...
To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs conta...
We proposed a method to quantify the yield of an IT-investment portfolio in an environment of uncertainty and risk. For various common implementation scenarios such as growing dem...