Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution ...
The current evolution of Information Technology leads to the increase of automatic data processing over multiple information systems. The data we deal with concerns sensitive infor...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the p...
Spatio-temporal data sets arise when time-varying physical fields are discretized for simulation or analysis. Examples of time-varying fields are isothermal regions in the sea or ...