Three Modern Roles for Logic in AI

We consider three modern roles for logic in artificial intelligence, which are based on the theory of tractable Boolean circuits: (1) logic as a basis for computation, (2) logic for learning from a combination of data and knowledge, and (3) logic for reasoning about the behavior of machine learning systems.Comment: To be published in PODS 202

European Regional Space Classification Regarding Smart Growth Level

The paper presented classification results including European regional space positional statistics regarding advancement and smart growth level in NUTS 2 regions. Regional smart growth covers three pillars: innovation, creativity (Knowledge Based Economy) and smart specialization illustrated by characteristics available in Eurostat data resources. These qualities constituted the basis for constructing aggregate measures for specific pillars and also for the purposes of regional classification. The results of obtained classes were assessed in an overall European space, in groups of regions distinguished in line with integration processes chronology and also in capital regions and these including the country capital, as well as in the system of Polish regions.Strategia Europa 2020, jako sukcesor Strategii Lizbońskiej, jest wizją społecznej gospodarki rynkowej dla Europy XXI wieku, obejmującą trzy powiązane priorytety: 1/ rozwój inteligentny: rozwój gospodarki opartej na wiedzy i innowacji; 2/ rozwój zrównoważony: wspieranie gospodarki efektywniej korzystającej z zasobów, bardziej przyjaznej środowisku i bardziej konkurencyjnej; 3/ rozwój sprzyjający włączeniu społecznemu: wspieranie gospodarki o wysokim poziomie zatrudnienia, zapewniającej spójność społeczną i terytorialną. W pracy przedstawiono wyniki klasyfikacji ze statystykami pozycyjnymi europejskiej przestrzeni regionalnej ze względu na stopień zaawansowania i poziom inteligentnego rozwoju w regionach szczebla NUTS 2. Rozwój inteligentny regionów uwzględnia trzy filary: innowacyjność, kreatywność (Gospodarka Oparta na Wiedzy) i inteligentną specjalizację ilustrowane charakterystykami znajdującymi się w zasobach informacyjnych Eurostatu. Cechy te stanowiły podstawę do konstrukcji miar agregatowych dla określonych filarów, a także do klasyfikacji regionów. Wyniki uzyskanych podziałów oceniono w całej europejskiej przestrzeni regionalnej, w grupach regionów wydzielonych zgodnie z chronologią procesów integracji, a także w regionach stołecznych i zawierających stolicę oraz w układzie regionów polskich

Optimized Framework based on Rough Set Theory for Big Data Pre-processing in Certain and Imprecise Contexts” -- Marie Sklodowska-Curie Project: Open Problems’

Peer reviewe

The Sequencing Problem in Sequential Investigation Processes

Many decision problems in various fields of application can be characterized as diagnostic problems trying to assess the true state (of the world) of given cases. The investigation of assessment criteria improves the initial information according to observed signal outcomes, which are related to the possible states. Such sequential investigation processes can be analyzed within the framework of statistical decision theory, in which prior probability distributions of classes of cases are updated, allowing for a sorting of particular cases into ever smaller subclasses. However, receiving such information causes investigation costs. Besides the question about the set of relevant criteria, this defines two additional problems of statistical decision problems: the optimal stopping of investigations and the optimal sequence of investigating a given set of criteria. Unfortunately, no solution exists with which the optimal sequence can generally be determined. Therefore, the paper characterizes the associated problems and analyzes existing heuristics trying to approximate an optimal solution.Decision-Making, Uncertainty, Information, Bayesian Analysis, Statistical Decision Theory

The SIMBAD astronomical database

Simbad is the reference database for identification and bibliography of astronomical objects. It contains identifications, `basic data', bibliography, and selected observational measurements for several million astronomical objects. Simbad is developed and maintained by CDS, Strasbourg. Building the database contents is achieved with the help of several contributing institutes. Scanning the bibliography is the result of the collaboration of CDS with bibliographers in Observatoire de Paris (DASGAL), Institut d'Astrophysique de Paris, and Observatoire de Bordeaux. When selecting catalogues and tables for inclusion, priority is given to optimal multi-wavelength coverage of the database, and to support of research developments linked to large projects. In parallel, the systematic scanning of the bibliography reflects the diversity and general trends of astronomical research. A WWW interface to Simbad is available at: http://simbad.u-strasbg.fr/SimbadComment: 14 pages, 5 Postscript figures; to be published in A&A

Astronomical Data Center Bulletin, volume 1, no. 1

Information about work in progress on astronomical catalogs is presented. In addition to progress reports, an upadated status list for astronomical catalogs available at the Astronomical Data Center is included. Papers from observatories and individuals involved with astronomical data are also presented

Automatic generation of assumptions for modular verification of software specifications

Model checking is a powerful automated technique mainly used for the verification of properties of reactive systems. In practice, model checkers are limited due to the state explosion problem. Modular verification based on the assume-guarantee paradigm mitigates this problem using a “divide and conquer” technique. Unfortunately, this approach is not automated, for the reason that the user must specify the environment model. In this paper, a novel technique is presented for automatically generating component assumptions based on the behaviour of the environment (the remainder of components of the systems). In a first phase, the environment of the component is computed using state space exploration techniques, and then the assumptions are generated as association rules of the component environment interface. This approach presents a number of advantages. Firstly, user assistance to specify assumptions is not necessary and assumption discharge is avoided. Secondly, the component assumptions are more restrictive and real, and therefore reduce the resources needed by the model checker. The technique is applied to the specification of a steam boiler syste