Modelling and analysis of Markov reward automata

Costs and rewards are important ingredients for many types of systems, modelling critical aspects like energy consumption, task completion, repair costs, and memory usage. This paper introduces Markov reward automata, an extension of Markov automata that allows the modelling of systems incorporating rewards (or costs) in addition to nondeterminism, discrete probabilistic choice and continuous stochastic timing. Rewards come in two flavours: action rewards, acquired instantaneously when taking a transition; and state rewards, acquired while residing in a state. We present algorithms to optimise three reward functions: the expected cumulative reward until a goal is reached, the expected cumulative reward until a certain time bound, and the long-run average reward. We have implemented these algorithms in the SCOOP/IMCA tool chain and show their feasibility via several case studies

A tutorial on interactive Markov chains

Interactive Markov chains (IMCs) constitute a powerful sto- chastic model that extends both continuous-time Markov chains and labelled transition systems. IMCs enable a wide range of modelling and analysis techniques and serve as a semantic model for many industrial and scientific formalisms, such as AADL, GSPNs and many more. Applications cover various engineering contexts ranging from industrial system-on-chip manufacturing to satellite designs. We present a survey of the state-of-the-art in modelling and analysis of IMCs.\ud We cover a set of techniques that can be utilised for compositional modelling, state space generation and reduction, and model checking. The significance of the presented material and corresponding tools is highlighted through multiple case studies

Трансформация социального управления в информационном обществе: к постановке проблем

Substantiated the idea that in today's information society is a transformation of social control in these conditions to create new types of control systems

Evaluación de hemerotecas de prensa digital: indicadores y ejemplos de buenas prácticas

La gran mayoría de los diarios digitales facilitan el acceso a la información retrospectiva mediante servicios de hemerotecas o archivos de prensa, un producto de notable interés para bibliotecas y otros servicios de información. El objetivo de este estudio es determinar cuáles son los indicadores fundamentales para la evaluación de hemerotecas digitales y, además, señalar ejemplos de buenas prácticas en España para cada uno de ellos. Se propone una relación de veintisiete indicadores agrupados en cuatro grandes apartados (aspectos generales, contenidos, sistema de consulta, y presentación de resultados), se describe cada uno de ellos y se incluye algún ejemplo de buena aplicación. Metodológicamente, se ha partido de la revisión de la bibliografía especializada en evaluación de recursos web, bases de datos y hemerotecas digitales, así como del análisis de hemerotecas de diarios de España y Catalunya. La utilización de estos indicadores puede ser de utilidad para que bibliotecas y otros servicios de información puedan orientar a sus usuarios en la consulta retrospectiva de información de prensa

Finite projective planes with a large abelian group

Markov automata (MA) constitute an expressive continuous-time compositional modelling formalism. They appear as semantic backbones for engineering frameworks including dynamic fault trees, Generalised Stochastic Petri Nets, and AADL. Their expressive power has thus far precluded them from effective analysis by probabilistic (and statistical) model checkers, stochastic game solvers, or analysis tools for Petri net-like formalisms. This paper presents the foundations and underlying algorithms for efficient MA modelling, reduction using static analysis, and most importantly, quantitative analysis. We also discuss implementation pragmatics of supporting tools and present several case studies demonstrating feasibility and usability of MA in practice