We present initial results from an international and multi-disciplinary research collaboration that aims at the construction of a reference corpus of web genres. The primary appli...
Georg Rehm, Marina Santini, Alexander Mehler, Pave...
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
The aim of this paper is to provide a sound framework for addressing a difficult problem: the automatic construction of an autonomous agent's modular architecture. We briefly...
The paper presents a database-based method to reduce the development time and project lead-time for large discreteevent simulation models of entire factories. The database used to...
Much recent research in decision theoretic planning has adopted Markov decision processes (MDPs) as the model of choice, and has attempted to make their solution more tractable by...