The MPSG (Message-based Part State Graph) model has been developed for the execution portion of shop-floor controllers that operate in a distributed and hierarchical control envir...
Devinder Thapa, Jaeil Park, Gi-Nam Wang, Dongmin S...
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
Abstract. While many higher-order interactive theorem provers include a choice operator, higher-order automated theorem provers currently do not. As a step towards supporting autom...