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This book comprehensively studies fuzzy temporal and spatial information, starting from the basics on fuzzy set theory and temporal/spatial reasoning, the development of a new model to represent fuzzy temporal/spatial information, the study of efficient and complete reasoning algorithms, and their application in an information retrieval context.

This useful volume presents the first approach that goes beyond merely representing information, by thoroughly addressing a variety of reasoning tasks. It also focuses on applications in the domain of information retrieval, and demonstrating the...

This book constitutes the refereed proceedings of the 10th International Conference on Scalable Uncertainty Management, SUM 2016, held in Nice, France, in September 2016.

The 18 regular papers and 5 short papers were carefully reviewed and selected from 35 submissions. Papers are solicited in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information. These include (but are not restricted to) applications in decision support systems, risk analysis, machine learning, belief networks, logics of uncertainty, belief...

Answer set programming (ASP) is a declarative language tailored towards solving combinatorial optimization problems. It has been successfully applied to e.g. planning problems, configuration and verification of software, diagnosis and database repairs. However, ASP is not directly suitable for modeling problems with continuous domains. Such problems occur naturally in diverse fields such as the design of gas and electricity networks, computer vision and investment portfolios. To overcome this problem we study FASP, a combination of ASP with fuzzy logic -- a class of manyvalued logics that can...

Suitable for modeling problems with continuous domains, this title shows how ASP techniques can be generalized to FASP, paving the way to implement fuzzy answer set solvers, that can take advantage of existing fuzzy reasoners.