The random k-SAT model is extensively used to compare satisfiability algorithms or to find the best settings for the parameters of some algorithm. Conclusions are derived from the...
The "minimum margin" of an ensemble classifier on a given training set is, roughly speaking, the smallest vote it gives to any correct training label. Recent work has sh...
We present a novel approach to plan recognition in which graph construction and analysis is used as a paradigm. We use a graph structure called a Goal Graph for the plan recogniti...
Probabilistic planning algorithms seek e ective plans for large, stochastic domains. maxplan is a recently developed algorithm that converts a planning problem into an E-Majsat pr...
One of the surprising findings from the study of CNF satisfiability in the 1990's has been the success of iterative repair techniques, and in particular of weighted iterative...