We present a general algorithm for synthesizing state invariants that speed up automated planners and have other applications in reasoning about change. Invariants are facts that ...
This paper compares three penalty terms with respect to the efficiency of supervised learning, by using first- and second-order learning algorithms. Our experiments showed that fo...
The robust deviation shortest path problem with interval data is studied in this paper. After the formulation of the problem in mathematical terms, an exact algorithm, based on a ...
Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
In this paper, we discuss a formalism for modeling regions that are exposed to movement or deformation. The basis of our formalism is the RCC theory, which uses topological relati...