Modeling worlds and actions under uncer­ tainty is one of the central problems in the framework of decision-theoretic planning. The representation must be general enough to capture real-world problems but at the same time it must provide a basis upon which theoretical results can be derived. The cen­ tral notion in the framework we propose here is that of the affine-operator, which serves as a ...

This report uses hypothetical decommissioning test cases to illustrate an uncertainty assessment methodology for dose assessments conducted as part of decommissioning analyses for NRC-licensed facilities. This methodology was pre sented previously in NUREG/CR-6656. The hypothetical test case source term and scenarios are based on an actual decommissioning case and the physical setting is based ...

During interactions with human consultants, people are used to providing partial and/ or inaccurate information, and still be under­ stood and assisted. We attempt to em­ ulate this capability of human consultants in computer consultation systems. In this paper, we present a mechanism for han­ dling uncertainty in plan recognition dur­ ing task-oriented consultations. The uncer­ tainty arises w...

We examine a new approach to modeling uncer­ tainty based on plausibility measures, where a plausibility measure just associates with an event its plausibility, an element is some partially or­ dered set. This approach is easily seen to gener­ alize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility measures. The lack of structure in a plau...

Farmers constantly face decisions about whether to invest in a new production method with increased risks and uncertainties or to maintain the current system without new risks and uncertainties. The possible method to evaluate a new business or investment opportunity is to use traditional discounted cash flow methods [23, 24]. Investment assessment is the very important part of the capital oper...

Measurements are frequently taken with little or no regard for the uncertainties or errors of those measurements, which may lead to incorrect conclusions and d ecisions. Professional societies today, including ASME, are becoming more and more concerned with measurement uncertainty. This paper is developed in full support of that concern. This paper discusses the value of an uncertainty analysis...

The significance of uncertainty analysis (UA) to quantify reliability of model simulations is being recognized. Consequently, literature on parameter and predictive uncertainty assessment of water resources models has been rising. Applications dealing with urban drainage systems are, however, very limited. This study applies formal Bayesian approach for uncertainty analysis of a widely used sto...

This report addresses issues related to the analysis of uncer tainty in dose assessments conducted as part of decommis sioning analyses. The analysis is limited to the hydrologic aspects of the exposure pathway involving infiltration of water at the ground surface, leaching of contaminants, and transport of contaminants through the groundwater to a point of exposure. The basic conceptual models...

The aggregation of conflicting preferences is a central problem in multiagent systems. The key difficulty is that the agents may report their preferences insincerely. Mechanism de­ sign is the art of designing the rules of the game so that the agents are motivated to re­ port their preferences truthfully and a (so­ cially) desirable outcome is chosen. We pro­ pose an approach where a mechanism ...

A perennial difficulty in the field of radioisotope scanning* is the fact that the requirements for resolu tion and number of counts are specified independ ently although everyone knows that both contribute to the ultimate picture quality. This difficulty results from the fact that the image degradation due to blurring and that due to statistics are not directly comparable. Blurring introduces ...