Computer interfaces provide an environment that allows for multiple objectively optimal solutions but individuals will, over time, use a smaller number of subjectively optimal solutions, developed as habits that have been formed and tuned by repetition. Designing an interface agent to provide assistance in this environment thus requires not only knowledge of the objectively optimal solutions, b...

Although the process of decision-making has been investigated for centuries, only in the last few decades have investigators systematically addressed how decisions are made in a dynamic, real-world environment. One of the most daunting challenges faced by decision support systems is a perpetual change in their environment. Existing decision support methodologies, tools, and frameworks are often...

In this study, a model was proposed based on the sustainable boundary approach, to provide decision support for reservoir ecological operation with dynamic Bayesian network. The developed in four steps: (1) calculating and verifying boundaries combination objectives of study area, (2) generating learning samples by establishing an optimal Monte Carlo simulation model, (3) training network examp...

Meetings are social events, were people exchange information. Often a summarization of the meeting is necessary, for example for people not attending the meeting or to fix decisions. A first step for the automatic analysis of the meetings is a segmentation into meeting group action events like discussion or presentation [4]. This structuring can then be used to produce an agenda and a summariza...

acceptance sampling models have been widely applied in companies for the inspection and testing the raw material as well as the final products. a number of lots of the items are produced in a day in the industries so it may be impossible to inspect/test each item in a lot. the acceptance sampling models only provide the guarantee for the producer and consumer that the items in the lots are acco...

EFFICIENT INFERENCE FOR HYBRID BAYESIAN NETWORKS Wei Sun, PhD George Mason University, 2007 Dissertation Director: Dr. KC Chang Uncertainty is everywhere in real life so we have to use stochastic model for most real-world problems. In general, both the systems mechanism and the observable measurements involve random noise. Therefore, probability theory and statistical estimation play important ...

There is accumulating evidence that prior knowledge about expectations plays an important role in perception. The Bayesian framework is the standard computational approach to explain how prior knowledge about the distribution of expected stimuli is incorporated with noisy observations in order to improve performance. However, it is unclear what information about the prior distribution is acquir...

This paper describes a process by which anthropologists, computer scientists, and social welfare case managers collaborated to build a stochastic model of welfare advising in Kentucky. In the process of collaboration, the research team rethought the Bayesian network model of Markov decision processes and designed a new knowledge elicitation format. We expect that this model will have wide appli...

Mammographic analysis is a difficult task due to the complexity of image interpretation. This results in diagnostic uncertainty, thus provoking the need for assistance by computer decision-making tools. Probabilistic modelling based on Bayesian networks is among the suitable tools, as it allows for the formalization of the uncertainty about parameters, models, and predictions in a statistical m...