This paper proposes an optimal approach to infinite-state action planning exploiting automata theory. State sets and actions are characterized by Presburger formulas and represent...
The generalization of policies in reinforcement learning is a main issue, both from the theoretical model point of view and for their applicability. However, generalizing from a se...
We propose a Bayesian undirected graphical model for co-training, or more generally for semi-supervised multi-view learning. This makes explicit the previously unstated assumption...
This paper presents a practical undertaking to solve an industry-specific problem of facility expansion through relocation of an existing production facility to a proposed new fac...
There are many planning applications that require an agent to coordinate its activities with processes that change continuously over time. Several proposals have been made for com...