Mostexisting decision-theoretic planners represent uncertainty about the state of the world with a precisely specified probability distribution over world states. This representat...
This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...
We examine a decision-theoretic Bayesian framework for the estimation of Sharpe Style portfolio weights of the MSCI sector returns. Following van Dijk and Kloek (1980) an appropri...
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
- Many exciting, emerging applications require that a group of agents share a coherent view of the world given spatial distribution, incomplete and uncertain sensors, and communica...
Robin Glinton, Katia P. Sycara, David Scerri, Paul...