A comprehensive comparison between generalized incidence calculus and Dempster-Shafer theory of evidence.

Dealing with uncertainty problems in intelligent systems has attracted a lot of attention in the AI community. Quite a few techniques have been proposed. Among them, the Dempster-Shafer theory of evidence (DS theory) has been widely appreciated. In DS theory, Dempster's combination rule plays a major role. However, it has been pointed out that the application domains of the rule are rather limited and the application of the theory sometimes gives unexpected results. We have previously explored the problem with Dempster's combination rule and proposed an alternative combination mechanism in generalized incidence calculus. In this paper we give a comprehensive comparison between generalized incidence calculus and the Dempster-Shafer theory of evidence. We first prove that these two theories have the same ability in representing evidence and combining DS-independent evidence. We then show that the new approach can deal with some dependent situations while Dempster's combination rule cannot. Various examples in the paper show the ways of using generalized incidence calculus in expert systems.

The ‘Public Interest’ Agency of International Organizations? The case of the OECD Principles of Corporate Governance

This article seeks to outline and explore some of the conditions necessary for International Organizations (IOs) to perform in a public interest fashion through a case study of the Principles of corporate governance formulated by the OECD. Rather than the more commonly documented pathological and dysfunctional behavioural forms of IOs, the case of the Principles, both in their formulation by the OECD, and in their assessment by the World Bank through the ROSC process, represent an episode of IO agency protecting and promoting a wider public interest. In exercising their agency, IO staff, have made the Principles more agreeable to a wider range of interested parties, giving them a general interest orientation, in accordance with a proceduralist definition of public interest. This case should therefore encourage IPE scholars to consider carefully and systematically the sets of circumstances and conditions, which might be required for IO agency to take more socially useful forms. In the final section, three indicators are identified which might be evaluated in future research into the positive public interest agency of IOs across a range of cases.

Bridging Jeffrey's Rule, AGM Revision and Dempster Conditioning in the Theory of Evidence

Belief revision characterizes the process of revising an agent’s beliefs when receiving new evidence. In the field of artificial intelligence, revision strategies have been extensively studied in the context of logic-based formalisms and probability kinematics. However, so far there is not much literature on this topic in evidence theory. In contrast, combination rules proposed so far in the theory of evidence, especially Dempster rule, are symmetric. They rely on a basic assumption, that is, pieces of evidence being combined are considered to be on a par, i.e. play the same role. When one source of evidence is less reliable than another, it is possible to discount it and then a symmetric combination operation
is still used. In the case of revision, the idea is to let prior knowledge of an agent be altered by some input information. The change problem is thus intrinsically asymmetric. Assuming the input information is reliable, it should be retained whilst the prior information should be changed minimally to that effect. To deal with this issue, this paper defines the notion of revision for the theory of evidence in such a way as to bring together probabilistic and logical views. Several revision rules previously proposed are reviewed and we advocate one of them as better corresponding to the idea of revision. It is extended to cope with inconsistency between prior and input information. It reduces to Dempster
rule of combination, just like revision in the sense of Alchourron, Gardenfors, and Makinson (AGM) reduces to expansion, when the input is strongly consistent with the prior belief function. Properties of this revision rule are also investigated and it is shown to generalize Jeffrey’s rule of updating, Dempster rule of conditioning and a form of AGM revision.

Theory of the Kinetics of Chemical Potentials in Heterogeneous Catalysis

Simple and powerful: The reaction kinetics at surfaces of heterogeneous catalysts is reformulated in terms of the involved chemical potentials. Based on this formulism, an approach of searching for good catalysts is proposed without recourse to extensive calculations of reaction barriers and detailed kinetic analyses. (see picture; R=reactant, I=surface intermediate, P=product, and =standard chemical potential).