Open-ended spoken interactions are typically characterised by both structural complexity and high levels of uncertainty, making dialogue management in such settings a particularly...
For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications wher...
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
We consider the problem of solving a nonhomogeneous infinite horizon Markov Decision Process (MDP) problem in the general case of potentially multiple optimal first period polic...
Torpong Cheevaprawatdomrong, Irwin E. Schochetman,...
In this article, we present an idea for solving deterministic partially observable markov decision processes (POMDPs) based on a history space containing sequences of past observat...