During the recent years of research on mobile agents, significant effort has been directed towards the identification of models of agent mobility suitable for network management a...
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, ...
: This paper presents an agent-based system for building and operating agent-based context-aware services in public spaces, including museums. The system provides users with agents...
Time information is critical for a variety of applications in distributed environments that facilitate pervasive computing and communication. This work describes and evaluates a no...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...