We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
We consider the fundamental problem of monitoring (i.e. tracking) the belief state in a dynamic system, when the model is only approximately correct and when the initial belief st...
Real world multiagent coordination problems are important issues for reinforcement learning techniques. In general, these problems are partially observable and this characteristic ...
Autocompletion is a widely deployed facility in systems that require user input. Having the system complete a partially typed "word" can save user time and effort. In th...
As spoken dialogue systems become deployed in increasingly complex domains, they face rising demands on the naturalness of interaction. We focus on system responsiveness, aiming t...