The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
We suggest in this article a new paradigm for the representation of data, which is best suited for the real-time visualization and sonorisation of complex systems, real or simulat...
Guillaume Hutzler, Bernard Gortais, Alexis Drogoul
The integration of data produced and collected across autonomous, heterogeneous web services is an increasingly important and challenging problem. Due to the lack of global identi...
Luis Gravano, Panagiotis G. Ipeirotis, Nick Koudas...
A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically r...
In spatiotemporal applications, meaningful changes vary according to object type, level of detail, and nature of application. In this paper, we introduce a dynamic classification ...
Giorgos Mountrakis, Peggy Agouris, Anthony Stefani...