We address the problem of building environment maps from ultrasonic range data obtained from multiple viewpoints. We present a novel environment modelling technique called the `response grid' that allows us to build occupancy maps in highly specular environments. We present two di erent approaches that utilise this technique: a Bayesian probabilisitic approach and a Dempster-Shafer evidential r...

The Dempster-Shafer theory of evidence (DS theory) is one of the major approaches for reasoning under uncertainty. Although in most of cases, the theory is regarded as a new terminology for dealing with uncertainty , it has been proved that DS theory is closed related to probability theory Fagin and Halpern, 1989]. In this paper, we discuss a probabilistic background of mass functions under Dem...

This paper presents a process model of plan inference for use in natural language consultation systems. It includes a strategy that can both defer unwarranted decisions about the relationship of a new action to the user’s overall plan and sanction rational default inferences. The paper describes an implementation of this strategy using the Dempster-Shafer theory of evidential reasoning. Our pro...

In this paper we present a methodology and discuss some implementation issues for a project on statistical/expert approach to data analysis and knowledge acquisition. We discuss some general assumptions underlying the project. Further, the requirements for a user-friendly computer assistant are specified along with the nature of tools aiding the researcher. Next we show some aspects of belief n...

In the domain of ubiquitous computing, the ability to identify the occurrence of situations is a core function of being 'contextaware'. Given the uncertain nature of sensor information and inference rules, reasoning techniques that cater for uncertainty hold promise for enabling the inference process. In our work, we apply the Dempster Shafer theory of evidence to determine situation occurrence...

Resolution is an often used method for deducation in propositional logic Here a proper organisation of deduction is proposed which avoids redundant computations It is based on a generic framework of decompositions and local computations as intro duced by Shafer Shenoy The system contains the two basic operations with informations namely marginalization or projection and combination the latter b...

This study sets out to establish a unified framework for causal and plausible reasoning. We identify a primitive set of causal roles which a condition may play in the inference. We also extend Dempster-Shafer theory to compose the belief in conclusion by the belief in rules and the belief in conditions. The combined framework permits us to express and propagate a scale of belief certainties in ...

Having a precise yet sound abstraction of the inputs of numerical programs is important to analyze their behavior. For many programs, these inputs are probabilistic, but the actual distribution used is only partially known. We present a static analysis framework for reasoning about programs with inputs given as imprecise probabilities: we define a collecting semantics based on the notion of pre...

Qualitative methods for reasoning under uncertainty may be helpful in situations where quantification of uncertainty is not appropriate. We demonstrate another use for qualitative models. The qualitative analysis of a quantitative model of uncertainty will reveal the qualitative behaviour of that model when new evidence is obtained. This qualitative behaviour can be compared with the specificat...

Abstrac t . In probabilistic reasoning when we have to build a probability distribution on some events and no further information is available, we then apply the insufficient reasoning principle; i.e. we assume that the events have equal opportunities to occur. In our previous work we have observed that in the Dempster-Shafer theory of evidence the principle is not applied when using Dempster's...