Titlebook: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundati; 17th International C Jesús Medina,Man

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A Bibliometric Analysis of the Explainable Artificial Intelligence Research Fieldlook at the contributions of scholars in XAI as well as in the subfields of AI that are mostly involved in the development of XAI systems. It is worthy to remark that we found out that about one third of contributions in XAI come from the fuzzy logic community. Accordingly, we went in depth with the

曲解

雄辯

Human Players Versus Computer Games Bots: A Turing Test Based on Linguistic Description of Complex P Restricted Equivalence Functions whose goal is to evaluate the “believability” of the computer games bots acting in a virtual world. A data-driven software architecture based on Linguistic Modelling of Complex Phenomena is also proposed which allows us to automatically generate bots behavior profil

BROOK

Reinterpreting Interpretability for Fuzzy Linguistic Descriptions of Datawe review the current state of linguistic descriptions of data and their use contexts as a standalone tool and as part of a natural language generation system. Then, we discuss the standard approach to interpretability for linguistic descriptions and introduce our complementary proposal, which descr

ACE-inhibitor

Personality Determination of an Individual Through Neural Networks the necessity of combining two psychological tests for carrying out personnel selection. From the assessment of the first test known as 16 Personality Factor we can directly obtain an appraisal of the individual’s personality type as the one given by the Enneagram Test, which now does not need to b

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侵略者

Tell Me Why: Computational Explanation of Conceptual Similarity Judgmentsroblem is, given a pair of concepts, to provide a score that expresses in how far the two concepts are similar. In order to explain how explanations are automatically built, we illustrate some basic features of ., the lexical resource that underlies our approach, and the main traits of the . system,

Grating

Multi-operator Decision Trees for Explainable Time-Series Classification challenge proposed by the industry to ease use of these tools by engineers and domain experts. In the paper we address the problem of generating interpretable classification of time-series data. We propose to extend the classical decision tree machine learning algorithm to Multi-operator Temporal D

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GROVE

Efficient Binary Fuzzy Measure Representation and Choquet Integral Learningr, the ChI incurs huge storage and computational burden due to its exponential complexity relative to . and, as a result, its calculation, storage, and learning becomes intractable for even modest sizes (e.g., .). Inspired by empirical observations in multi-sensor fusion and the more general need to