: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
This paper presents an analysis of static and dynamic organizational structures for naturally distributed, homogeneous, cooperative problem solving environments, exemplified by di...
We present Variable Influence Structure Analysis, or VISA, an algorithm that performs hierarchical decomposition of factored Markov decision processes. VISA uses a dynamic Bayesia...
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
This paper presents a sequential two-stage strategy for the stochastic synthesis of chemical processes in which flexibility and ability to adjust manipulated variables are taken i...