Abstract In Evidence theory, several conditioning rules for updating belief have been proposed, including Dempster’s rule of conditioning. The paper views the conditioning rules proposed so far and proposes a new rule of conditioning based on three requirements. Then, it generalizes the rule to be applied to the case where condition is given by an uncertain belief. The paper also discusses a fe...

Mingchuan Zhang and Su-shing Chen Department of Computer Science University of North Carolina Charlotte, NC 28223 In this paper, we present some results of evidential reasoning m understanding multispectral images of remote sensing systems. The Dempster-Shafer approach of combination of evidences is pursued to yield contextual classification results, which are compared with previous results of ...

In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reasoning. We prove the existence of a collection of importance functions that are close to the optimal importance function under evidential reasoning. Based on this theoretic result we derive the RIS algorithm. RIS approach...

Reasoning about causality is an interesting application area of formal nonmonotonic theories. Here we focus our attention on a certain aspect of causal reasoning, namely causaZ asymmetry. In order to provide a qualitative account of causal asymmetry, we present a justification-based approach that uses circurnscription to obtain the minimality of causes. We define the notion of causal and eviden...

Evidential Reasoning provides quantitative enhancements to the reasoning formalisms which use set based algebra. Interval Algebra is a Temporal Reasoning formalism which uses sets as representation forms and employs tools based on set operations. The traditional reasoning in the Interval Algebra is to apply a search process, Backtrack search, which takes exponential runtime. We augment Interval...

In this paper, we present two methods to provide explanations for reasoning with be­ lief functions in the valuation-based systems. One approach, inspired by Strat's method, is based on sensitivity analysis, but its com­ putation is simpler thus easier to implement than Strat 's. The other one is to examine the impact of evidence on the conclusion based on the measure of the information content...

Particle filtering has come into favor in the computer vision community with the CONDENSATION algorithm. Perhaps the main reason for this is that it relaxes many of the assumptions made with other tracking algorithms, such as the Kalman filter. It still places a strong requirement on the ability to model the observations and dynamics of the systems with conditional probabilities. In practice th...

BPS, the Bayesian Problem Solver, applies probabilistic inference and decision-theore­ tic control to flexible, resource-constrained problem-solving. This paper focuses on the Bayesian inference mechanism in BPS, and contrasts it with those of traditional heuristic search techniques. By performing sound inference, BPS can outperform traditional techniques with signifi­ cantly less computational...

What is the relation between language and thought? Specifically, how do linguistic and conceptual representations make contact during language learning? This paper addresses these questions by investigating the acquisition of evidentiality (the linguistic encoding of information source) and its relation to children's evidential reasoning. Previous studies have hypothesized that the acquisition ...