A survey of qualitative spatial representations

Representation and reasoning with qualitative spatial relations is an important problem in artificial intelligence and has wide applications in the fields of geographic information system, computer vision, autonomous robot navigation, natural language understanding, spatial databases and so on. The reasons for this interest in using qualitative spatial relations include cognitive comprehensibility, efficiency and computational facility. This paper summarizes progress in qualitative spatial representation by describing key calculi representing different types of spatial relationships. The paper concludes with a discussion of current research and glimpse of future work

Wittgenstein and Biolinguistics: Building upon the Second Picture Theory

Circa 1930, Wittgenstein began to develop a theory of semantics in terms of distinct representational systems (calculi) each constructed from measure-ment scales. Impressed by the heterogeneity of measurement scaling, he eventually abandoned the effort. However, such a project can be continued in the light of later developments in measurement theory. Any remaining heterogeneity can be accounted for, plausibly enough, in terms of the facultative nature of the mind/brain. Developing such a theory is potentially a contribution to biolinguistics. The symmetries and asymmetries of the measurement scales suggest self-organization in brain activity, further suggesting a connection between such a neo-Wittgensteinian approach to the thought systems and minimalist approaches to syntax

Introductory lectures to loop quantum gravity

We give a standard introduction to loop quantum gravity, from the ADM variables to spin network states. We include a discussion on quantum geometry on a fixed graph and its relation to a discrete approximation of general relativity.Comment: Based on lectures given at the 3eme Ecole de Physique Theorique de Jijel, Algeria, 26 Sep -- 3 Oct, 2009. 52 pages, many figures. v2 minor corrections. To be published in the proceeding

Finite-time adaptive synchronization of fractional-order delayed quaternion-valued fuzzy neural networks

Based on direct quaternion method, this paper explores the finite-time adaptive synchronization (FAS) of fractional-order delayed quaternion-valued fuzzy neural networks (FODQVFNNs). Firstly, a useful fractional differential inequality is created, which offers an effective way to investigate FAS. Then two novel quaternion-valued adaptive control strategies are designed. By means of our newly proposed inequality, the basic knowledge about fractional calculus, reduction to absurdity as well as several inequality techniques of quaternion and fuzzy logic, several sufficient FAS criteria are derived for FODQVFNNs. Moreover, the settling time of FAS is estimated, which is in connection with the order and initial values of considered systems as well as the controller parameters. Ultimately, the validity of obtained FAS criteria is corroborated by numerical simulations