54k citations · 58.7k across the 46 of their papers we have counts for
8 papers · 1 filter
Optimal Value of Information in Graphical Models
Andreas Krause, Carlos Guestrin
Many real-world decision making tasks require us to choose among several expensive observations. In a sensor network, for example, it is important to select the subset of sensors t…
Robust Combination of Local Controllers
Carlos E. Guestrin, Dirk Ormoneit
Planning problems are hard, motion planning, for example, isPSPACE-hard. Such problems are even more difficult in the presence of uncertainty. Although, Markov Decision Processes (…
Distributed Planning in Hierarchical Factored MDPs
Carlos E. Guestrin, Geoffrey Gordon
We present a principled and efficient planning algorithm for collaborative multiagent dynamical systems. All computation, during both the planning and the execution phases, is dist…
Robust Probabilistic Inference in Distributed Systems
Mark Paskin, Carlos E. Guestrin
Probabilistic inference problems arise naturally in distributed systems such as sensor networks and teams of mobile robots. Inference algorithms that use message passing are a natu…
Solving Factored MDPs with Continuous and Discrete Variables
Carlos E. Guestrin, Milos Hauskrecht, Branislav Kveton
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods c…
Near-optimal Nonmyopic Value of Information in Graphical Models
Andreas Krause, Carlos E. Guestrin
A fundamental issue in real-world systems, such as sensor networks, is the selection of observations which most effectively reduce uncertainty. More specifically, we address the lo…