Evidential Reasoning
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Recent papers in Evidential Reasoning
Resolving domain incompatibility among independently developed databases often involves uncertain information. DeMichiel (1989) showed that uncertain information can be generated by the mapping of conflicting attributes to a common... more
Como un intento de responder a la pregunta que titula este trabajo, haré una breve reseña de los aspectos principales que particularizan al razonamiento probatorio judicial en relación con el realizado, con el mismo objeto, por fuera de... more
This paper introduces a subjective logic based argumentation framework primarily targeted at evidential reasoning. The framework explicitly caters for argument schemes, accrual of arguments, and burden of proof; these concepts appear in... more
The evidential reasoning (ER) rule for multi-attribute classification has been recently developed, and has enhanced the properties of the Dempster's rule through defining the weight and reliability of the evidence. This paper aims to... more
Witness credibility is important for establishing testimonial value. The story model posits that people construct narratives from evidence but does not explain how credibility is assessed. Formal approaches use Bayesian networks (BN) to... more
Recent research (Pilditch, Fenton, & Lagnado, 2019) shows that people are susceptible to zero-sum thinking in evidence evaluation, where they dismiss or underweight the probative value of evidence that is equally predicted by multiple... more
The evidence theory and its propositional conflict redistribution variant rules are mathematical formalisms used to represent uncertain as well as ambiguous data. The evidence combination rules proposed in these formalisms do not satisfy... more
With an aim of having a normal behavior in combination of bodies of evidence, this paper proposes a new combination rule which includes the cardinality of focal set elements in conjunctive operation and the conflict redistribution to all... more
Abstract: In this paper, a clustering based machine learning algorithm called Clustering Algorithm System (CAS) is introduced. The CAS algorithm is tested to evaluate its performance and find fruitful results. We have been presented some... more
The location of any business facility plays a pivotal role in the success of the business and it is one of the major considerations in subjects such as business strategy, operations management and economics. This paper proposes the use of... more
Machine-learning research is to study and apply the computer modeling of learning processes in their multiple manifestations, which facilitate the development of intelligent system. In this paper, we have introduced a clustering based... more
This paper describes an on-going effort to build an Adaptable Data Fusion Testbed (ADFT) based on a Knowledge-Based System (KBS) BlackBoard (BB) architecture to perform data fusion of imaging and nonimaging sensors present on-board the... more
Various demographic and medical factors can be linked to severe deterioration of patients suffering from traumatic injuries. Accurate identification of the most relevant variables is essential for building more accurate prediction models... more
Most inferentialists hope to bypass givenness by tracking the conditionals claimants are implicitly committed to. I argue that this approach is underdetermined because one can always construct parallel trees of conditionals. I illustrate... more