While the notion of a cooperative response has been the focus of considerable research in natural language dialogue systems, there has been little empirical work demonstrating how...
This paper presents a data-driven approach for segmenting range data to enable a humanoid robot to perform interactive domestic tasks. Range data is segmented into geometric primi...
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...