Today AI systems are rarely made without Machine Learning (ML) and this inspires us to explore what aptly called composite argumentation with ML components. Concretely, against two theoretical backdrops of PABA (Probabilistic Assumption-based Argumentation) DST (Dempster-Shafer Theory), we present a framework for such c-PABA. It is argued that c-PABA lends itself development tool as well demons...

This chapter presents a general overview and foundations of the DSmT, i.e. the recent theory of plausible and paradoxical reasoning developed by the authors, specially for the static or dynamic fusion of information arising from several independent but potentially highly conflicting, uncertain and imprecise sources of evidence. We introduce and justify here the basis of the DSmT framework with ...

This chapter presents a general overview and foundations of the DSmT, i.e. the recent theory of plausible and paradoxical reasoning developed by the authors, specially for the static or dynamic fusion of information arising from several independent but potentially highly conflicting, uncertain and imprecise sources of evidence. We introduce and justify here the basis of the DSmT framework with ...

An algorithm for updating the evidence in the Dempster–Shafer theory is presented. The algorithm is based on an idea of indices. These indices are used to code the process of reasoning under uncertainty (the combination of evidence)using the Dempster-Shafer theory. The algorithm allows to carry out the reasoning with updating the evidence in much more efficient way than using the original Demps...

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This chapter presents several classes of fusion problems which cannot be directly approached by the classical mathematical theory of evidence, also known as Dempster-Shafer Theory (DST), either because Shafer’s model for the frame of discernment is impossible to obtain, or just because Dempster’s rule of combination fails to provide coherent results (or no result at all). We present and discuss...

The combination of sources of evidence with reliability has been widely studied within the framework of Dempster-Shafer theory (DST), which has been employed as a major method for integrating multiple sources of evidence with uncertainty. By the fact that sources of evidence may also be different in importance, for example in multi-attribute decision making (MADM), we propose the importance dis...

Dempster-Shafer theory is one of the main tools for reasoning about data obtained from multiple sources, subject to uncertain information. In this work abstract algebraic properties of the Dempster-Shafer set of mass assignments are investigated and compared with the properties of the Bayes set of probabilities. The Bayes set is a special case of the Dempster-Shafer set, where all non-singleton...

This paper presents several classes of fusion problems which cannot be directly attacked by the classical mathematical theory of evidence, also known as the Dempster-Shafer Theory (DST) either because the Shafer’s model for the frame of discernment is impossible to obtain or just because the Dempster’s rule of combination fails to provide coherent results (or no result at all). We present and d...

In this paper, one conflict context reasoning method based on Dempster-Shafer theory is proposed. Firstly the context conflict problems are illustrated and partitioned based on theory of evidence. Then the context model combined with Dempster-Shafer theory is presented and applied to the reasoning method based on Dempster rule of combination. The effectiveness of this method is verified with a ...