1,721,104 research outputs found
Conceptual Aspects and Considerations for the Risk Analysis of Complex Structural Systems such as Long Suspension Bridges.
No full textICOSSAR 2005, G. Augusti, G.I. Schuëller, M. Ciampoli (eds
Concept Combination in Weighted DL
No full textBuilding on previous work on Weighted Description Logic (WDL), we present and assess an algorithm for concept combination grounded in the experimental research in cognitive psychology. Starting from two WDL formulas representing concepts in a way similar to Prototype Theory and a knowledge base (KB) modelling background knowledge, the algorithm outputs a new WDL formula which represent the combination of the input concepts. First, we study the logical properties of the operator defined by our algorithm. Second, we collect data on the prototypical representation of concepts and their combinations and learn WDL formulas from them. Third, we evaluate our algorithm and the role of the KB by comparing the algorithm’s outputs with the learned WDL formulas
Investigating Alternative Phase Planes for Assessing Vehicle Stability
No full textThis paper discusses the possibility of assessing vehicle stability by means of unconventional graphical methodologies and defining a region of stability of the vehicle, using only yaw rate, lateral acceleration and sideslip rate. The three-dimensional β-r-β ̇ phase surface is investigated, relating trajectories in the r-β ̇ plane to their β values. The r-β ̇ phase plane is investigated for different tyre models and tyre-road friction conditions. A new stability region is proposed
Evaluating the Interpretability of Threshold Operators
No full textWeighted Threshold Operators are n-ary operators that compute a weighted sum of their arguments and verify whether it reaches a certain threshold. They have been extensively studied in the area of circuit complexity theory, as well as in the neural network community under the name of perceptrons. In Knowledge Representation, they have been introduced in the context of standard Description Logics (DL) languages by adding a new concept constructor, the Tooth operator (∇∇ ). Tooth expressions can provide a powerful yet natural tool to represent local explanations of black box classifiers in the context of Explainable AI. In this paper, we present the result of a user study in which we evaluated the interpretability of tooth expressions, and we compared them with Disjunctive Normal Forms (DNF). We evaluated interpretability through accuracy, response time, confidence, and perceived understandability by human users. We expected tooth expressions to be generally more interpretable than DNFs. In line with our hypothesis, the study revealed that tooth expressions are generally faster to use, and that they are perceived as more understandable by users who are less familiar with logic. Our study also showed that the type of task, the type of DNF, and the background of the respondents affect the interpretability of the formalism used to represent explanations
Introduction / Introduzione (coautori: A.M. D’Achille, M. Preti-Hamard, M. Righetti, G. Toscano)
No full textIntroduzione agli Atti del Convegno dedicato all'erudito francese Aubin-Louis Millin, svoltosi a Parigi e Roma nel 200
- …
