Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Recently, several approaches for updating knowledge bases represented as logic programs have been proposed. In this paper, we present a generic framework for declarative specifica...
Thomas Eiter, Michael Fink, Giuliana Sabbatini, Ha...
This paper presents an object oriented framework that facilitates modeling inventory systems whose policy updating is driven by forecast estimates. In an inventory system, the for...
Manuel D. Rossetti, Vijith Varghese, Mehmet Miman,...
As a user attention has become a precious resource, a special care has to be taken to reduce the time needed for answering queries in P2P networks. Existing solutions are usually ...
We try to analyze a generic model for 2-tier distributed systems, exploring the possibility of optimal cluster sizes from an information management perspective, such that the over...