Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have a...
In this paper we describe an algorithm to approximately solve a class of semidefinite programs called covering semidefinite programs. This class includes many semidefinite programs...
In this work we focus on efficient heuristics for solving a class of stochastic planning problems that arise in a variety of business, investment, and industrial applications. The...
We exploit the recently proposed Concept Abduction inference service in Description Logics to solve Concept Covering problems. We propose a framework and polynomial greedy algorit...
Tommaso Di Noia, Eugenio Di Sciascio, Francesco M....
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...