Abstract. The aim of this paper is to study semantic notions of modularity in description logic (DL) terminologies and reasoning problems that are relevant for modularity. We defin...
Boris Konev, Carsten Lutz, Dirk Walther, Frank Wol...
A new language and inference algorithm for stochastic modeling is presented. This work refines and generalizes the stochastic functional language originally proposed by [1]. The l...
This paper describes some of the interactions of model learning algorithms and planning algorithms we have found in exploring model-based reinforcement learning. The paper focuses...
The ability to answer prediction questions is crucial to reasoning about physical systems. A prediction question poses a hypothetical scenario and asks for the resulting behavior ...
—In this paper we present findings from our windowing BitTorrent simulations and show that by carefully optimizing other factors a reasonable level of performance can be achieved...
Petri Savolainen, Niklas Raatikainen, Sasu Tarkoma