We present an architectural approach to learning problem solving skills from demonstration, using internal models to represent problem-solving operational knowledge. Internal forwa...
Haris Dindo, Antonio Chella, Giuseppe La Tona, Mon...
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
We give an overview of GRIP, a symmetry reduction tool for the probabilistic model checker PRISM, together with experimental results for a selection of example specifications. 1 ...
Disjunctive Logic Programming (DLP) under the consistent answer set semantics is an advanced formalism for knowledge representation and reasoning. It is, under widely believed assu...
Abstract. Scheduling the execution of multiple concurrent tasks on shared resources such as CPUs and network links is essential to ensuring the reliable operation of many autonomic...
Terry Tidwell, Robert Glaubius, Christopher D. Gil...