In this paper, partial knowledge about the possible transitions which can take place in a dynamical environment is represented by a set of pairs of propositional formulae, with th...
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Abstract—This paper introduces a knowledge-driven approach to real-time, continuous activity recognition based on multisensor data streams in smart homes. The approach goes beyon...
We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in ...
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C...
In this paper we combine existing work in the area of social laws with a framework for reasoning about knowledge in multi-agent systems. The unifying framework in which this is do...
Wiebe van der Hoek, Mark Roberts, Michael Wooldrid...