Spoken dialogue managers have benefited from using stochastic planners such as Markov Decision Processes (MDPs). However, so far, MDPs do not handle well noisy and ambiguous speec...
We present an algorithm that derives actions' effects and preconditions in partially observable, relational domains. Our algorithm has two unique features: an expressive rela...
This paper studies the problem of model-based testing of real-time systems that are only partially observable. We model the System Under Test (SUT) using Timed Game Automata (TGA)...
Alexandre David, Kim Guldstrand Larsen, Shuhao Li,...
Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...
Partially observed actions are observations of action executions in which we are uncertain about the identity of objects, agents, or locations involved in the actions (e.g., we kn...