Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...
The Workshop included an extended group of presentations by selected US government agencies and an invited guest from the European Community. These presentations, amplified in the...
The traditional approach to building Bayesian networks is to build the graphical structure using a graphical editor and then add probabilities using a separate spreadsheet for eac...
As the scale and scope of distributed and multi-agent systems grow, it becomes increasingly important to design and manage the participants' interactions. The potential for b...