Abstract. A new algorithm is presented for detecting whether a particular computation of an asynchronous distributed system satisfies Poss Φ (read “possibly Φ”), meaning the...
We apply a constrained Hidden Markov Model architecture to the problem of simultaneous localization and surveying from sensor logs of mobile agents navigating in unknown environmen...
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Abstract. This paper presents an approach for formalizing the RM-ODP (Reference Model for Open Distributed Processing), an ISO and ITU standard. The goal of this formalization is t...
Andrey Naumenko, Alain Wegmann, Guy Genilloud, Wil...
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...