Previous work on sensitivity analysis in Bayesian networks has focused on single parameters, where the goal is to understand the sensitivity of queries to single parameter changes...
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...
We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the cross-sum step of the dyn...
Simulation is a powerful tool that helps decision makers in business and industry to solve difficult and complex problems, reduce cost, improve quality and productivity, and short...
Unit resolution is arguably the most useful known algorithm for tractable reasoning in propositional logic. Intuitively, if one knows a, b, and a b c, then c should be an obviou...