PLAN is a language designed for programming active networks, and can more generally be regarded as a model of mobile computation. PLAN generalizes the paradigm of imperative funct...
Markov decision processes (MDPs) and contingency planning (CP) are two widely used approaches to planning under uncertainty. MDPs are attractive because the model is extremely gen...
We study the stochastic machine replenishment problem, which is a canonical special case of closed multiclass queuing systems in Markov decision theory. The problem models the sche...
Much has been made of the need for academic planning research to orient towards real-world applications. In this paper, we relate our experience in adapting domain-independent pla...
This article illustrates the complexities of real-world planning and how we can create AI planning systems to address them. We describe the IMACS Project (Interactive Manufacturab...