Nachtrag: Monetisierung des griechischen Staatsvermögens in Form einer Parallelwährung

In Ergänzung zu den Beiträgen im Schnelldienst 23/2011 schlägt Udo Neuhäußer, Bundesministerium für Wirtschaft und Technologie, vor, das griechische Staatsvermögen in ein Sondervermögen einzubringen und zur Deckung mit einer griechischen Parallelwährung »Neue Drachme« zu unterlegen. Durch diese Monetisierung des Staatsvermögens kann das Land in großem Umfang entschuldet und ihm eine verbesserte Erholungsperspektive eröffnet werden.Währungswettbewerb, Öffentliches Vermögen, Öffentliche Schulden, Griechenland

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

Towards Erlang Verification by Term Rewriting

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-14125-1_7This paper presents a transformational approach to the verification of Erlang programs. We define a stepwise transformation from (first-order) Erlang programs to (non-deterministic) term rewrite systems that compute an overapproximation of the original Erlang program. In this way, existing techniques for term rewriting become available. Furthermore, one can use narrowing as a symbolic execution extension of rewriting in order to design a verification technique. We illustrate our approach with some examples, including a deadlock analysis of a simple Erlang program.Vidal Oriola, GF. (2013). Towards Erlang Verification by Term Rewriting. En Logic-Based Program Synthesis and Transformation. Springer. 109-126. doi:10.1007/978-3-319-14125-1_7S109126Albert, E., Arenas, P., Gómez-Zamalloa, M.: Symbolic Execution of Concurrent Objects in CLP. In: Russo, C., Zhou, N.-F. (eds.) PADL 2012. 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Proc. of the 9th International Workshop on Functional and Logic Programming (WFLP 2000), pp. 42–55 (2000)Felleisen, M., Friedman, D.P., Kohlbecker, E.E., Duba, B.F.: A syntactic theory of sequential control. Theor. Comput. Sci. 52, 205–237 (1987)Fredlund, L.-A., Svensson, H.: McErlang: a model checker for a distributed functional programming language. In: Hinze, R., Ramsey, N. (eds). In: Proc. of ICFP 2007, pp. 125–136. ACM (2007)Giesl, J., Arts, T.: Verification of Erlang Processes by Dependency Pairs. Appl. Algebra Eng. Commun. Comput. 12(1/2), 39–72 (2001)Hanus, M. (ed.): Curry: An integrated functional logic language (vers. 0.8.3) (2012), http://www.curry-language.orgHuch, F.: Verification of Erlang Programs using Abstract Interpretation and Model Checking. In: Rémi, D., Lee, P. (eds.) Proc. of ICFP 1999, pp. 261–272. ACM (1999)J.-M., H.: Canonical forms and unification. In: Bibel, W., Kowalski, R. (eds.) 5th Conference on Automated Deduction Les Arcs. LNCS, pp. 318–334. 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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

A hemimetric extension of simulation for semi-markov decision processes

Semi-Markov decision processes (SMDPs) are continuous-time Markov decision processes where the residence-time on states is governed by generic distributions on the positive real line. In this paper we consider the problem of comparing two SMDPs with respect to their time-dependent behaviour. We propose a hemimetric between processes, which we call simulation distance, measuring the least acceleration factor by which a process needs to speed up its actions in order to behave at least as fast as another process. We show that this distance can be computed in time O(n2(f(l)+k)+mn7), where n is the number of states, m the number of actions, k the number of atomic propositions, and f(l) the complexity of comparing the residence-time between states. The theoretical relevance and applicability of this distance is further argued by showing that (i) it is suitable for compositional reasoning with respect to CSP-like parallel composition and (ii) has a logical characterisation in terms of a simple Markovian logic

Bisimulation and logical preservation for continuous-time Markov decision processes

This paper introduces strong bisimulation for continuous-time Markov decision processes (CTMDPs), a stochastic model which allows for a nondeterministic choice between exponential distributions, and shows that bisimulation preserves the validity of CSL. To that end, we interpret the semantics of CSL - a stochastic variant of CTL for continuous-time Markov chains - on CTMDPs and show its measure theoretic soundness. The main challenge faced in this paper is the proof of logical preservation that is substantially based on measure theory

Time-Bounded Reachability in Continuous-Time Markov Decision Processes

This paper solves the problem of computing the maximum and minimum probability to reach a set of goal states within a given time bound for locally uniform continuous-time Markov decision processes (CTMDPs). As this model allows for nondeterministic choices between exponentially delayed transitions, we define total time positional (TTP) schedulers which rely on the CTMDP’s current state and the total elapsed time when taking a decision. In this paper, TTP schedulers are proved to be sufficient to maximize timed reachability even w.r.t. fully time- and history-dependent schedulers; further, they allow us to derive a fixed point characterization of the optimal timed-reachability probability. The main contribution of this paper is a discretization technique which, for an a priori given error bound ε, induces a discrete-time MDP that approximates the optimal timed reachability probability in the underlying CTMDP up to ε