We introduce and develop a topological semantics of conservativity logics interpretability logics. prove the compactness theorem consistent normal extensions logic $\mathbf{CL}$ by extending Shehtman's ultrabouquet construction method to our framework. As consequence, we that several such as $\mathbf{IL}$, $\mathbf{ILM}$, $\mathbf{ILP}$ $\mathbf{ILW}$ are strongly complete with respect semantics.

The past decade has witnessed wide applications of deep neural networks in anomaly detection. However, the dearth interpretability often hinders their reliability, especially for industrial where practical users heavily rely on interpretable methods to provide explanations decision-making. In this paper, we propose a reconstruction-based approach unsupervised detection anomalies defect data. Ou...

A miracle happens In one hand we have a class of marvelously complex theories in predicate logic theories with su cient coding potential like PA Peano Arithmetic or ZF Zermelo Fraenkel Set Theory In the other we have certain modal propositional theories of striking simplicity We translate the modal operators of the modal theories to certain speci c xed de ned predicates of the predicate logical...

This paper presents work using crowdsourcing to assess explanations for supervised text classification. In this paper, an explanation is defined to be a set of words from the input text that a classifier or human believes to be most useful for making a classification decision. We compared two types of explanations for classification decisions: human-generated and computer-generated. The compari...

Article history: Available online 4 March 2011

System modeling with fuzzy rule-based systems (FRBSs), i.e. fuzzy modeling (FM), usually comes with two contradictory requirements in the obtained model: the interpretability, capability to express the behavior of the real system in an understandable way, and the accuracy, capability to faithfully represent the real system. While linguistic FM (mainly developed by linguistic FRBSs) is focused o...

Human-robot interactive decision-making is increasingly becoming ubiquitous, and trust an influential factor in determining the reliance on autonomy. However, it not reasonable to systems that are beyond our comprehension, typical machine learning data-driven black-box paradigms impede interpretability. Therefore, critical establish computational trustworthy mechanisms enhanced by interpretabil...