TL;DR: This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
Abstract: Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [11, 12], is a new mathematical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
TL;DR: This paper reviewed the variety of definitions of resilience within sustainability science and suggested a typology according to the specific degree of normativity of the concept of resilience, and argued that a clearly specified, descriptive concept is critical in providing a counterbalance to the use of resilience as a vague boundary object.
Abstract: This article reviews the variety of definitions proposed for "resilience" within sustainability science and suggests a typology according to the specific degree of normativity. There is a tension between the original descriptive concept of resilience first defined in ecological science and a more recent, vague, and malleable notion of resilience used as an approach or boundary object by different scientific disciplines. Even though increased conceptual vagueness can be valuable to foster communication across disciplines and between science and practice, both conceptual clarity and practical relevance of the concept of resilience are critically in danger. The fundamental question is what conceptual structure we want resilience to have. This article argues that a clearly specified, descriptive concept of resilience is critical in providing a counterbalance to the use of resilience as a vague boundary object. A clear descriptive concept provides the basis for operationalization and application of resilience within ecological science.
TL;DR: In this paper, the authors focus on the problem of efficiently allocating resources to the production of information and examine the mistakes and the vagueness associated with this approach, which is a critique of Arrow's analysis.
Abstract: The importance of bringing economic analysis to bear on the problems of efficient economic organization hardly requires comment, but there is a need to review the manner in which the notion of efficiency is used in these problems. The concept of efficiency has been abused frequently because of the particular approach used by many analysts. My aim is to examine the mistakes and the vagueness associated with this approach. I shall focus attention on the problem of efficiently allocating resources to the production of information because in this case the issues stand out clearly. Since Kenneth J. Arrow’s paper ‘Economic Welfare and the Allocation of Resources for Invention’1 has been most influential in establishing the dominant viewpoint about this subject, my commentary necessarily is a critique of Arrow’s analysis.
TL;DR: The authors investigated the way that linguistic expressions influence vagueness, focusing on the interpretation of the positive (unmarked) form of gradable adjectives, and showed that the difference between relative and absolute adjectives in the positive form stems from the interaction of lexical semantic properties.
Abstract: This paper investigates the way that linguistic expressions influence vagueness, focusing on the interpretation of the positive (unmarked) form of gradable adjectives. I begin by developing a semantic analysis of the positive form of ‘relative’ gradable adjectives, expanding on previous proposals by further motivating a semantic basis for vagueness and by precisely identifying and characterizing the division of labor between the compositional and contextual aspects of its interpretation. I then introduce a challenge to the analysis from the class of ‘absolute’ gradable adjectives: adjectives that are demonstrably gradable, but which have positive forms that relate objects to maximal or minimal degrees, and do not give rise to vagueness. I argue that the truth conditional difference between relative and absolute adjectives in the positive form stems from the interaction of lexical semantic properties of gradable adjectives—the structure of the scales they use—and a general constraint on interpretive economy that requires truth conditions to be computed on the basis of conventional meaning to the extent possible, allowing for context dependent truth conditions only as a last resort.