GCSRL - A Logic for Stochastic Reward Models with Timed and Untimed Behaviour

In this paper we define the logic GCSRL (generalised continuous stochastic reward logic) that provides means to reason about systems that have states which sojourn times are either greater zero, in which case this sojourn time is exponentially distributed (tangible states), or zero (vanishing states).\ud In case of generalised stochastic Petri nets (GSPNs) and stochastic process algebras it turned out that these vanishing states can be very useful when it comes to define system behaviour. In the same way these states are useful for defining system properties using stochastic logics. We extend both the semantic model and the semantics of CSRL such that it allows to attach impulse rewards to transitions emanating from vanishing states. We show by means of a small example how model checking GCSRL formulae works

SPDL Model Checking via Property-Driven State Space Generation

In this report we describe how both, memory and time requirements for stochastic model checking of SPDL (stochastic propositional dynamic logic) formulae can significantly be reduced. SPDL is the stochastic extension of the multi-modal program logic PDL.\ud SPDL provides means to specify path-based properties with or without timing restrictions. Paths can be characterised by so-called programs, essentially regular expressions, where the executability can be made dependent on the validity of test formulae. For model-checking SPDL path formulae it is necessary to build a product transition system (PTS)\ud between the system model and the program automaton belonging to the path formula that is to be verified.\ud In many cases, this PTS can be drastically reduced during the model checking procedure, as the program restricts the number of potentially satisfying paths. Therefore, we propose an approach that directly generates the reduced PTS from a given SPA specification and an SPDL path formula.\ud The feasibility of this approach is shown through a selection of case studies, which show enormous state space reductions, at no increase in generation time.\u

Extending the Logic IM-SPDL with Impulse and State Rewards

This report presents the logic SDRL (Stochastic Dynamic Reward Logic), an extension of the stochastic logic IM-SPDL, which supports the specication of complex performance and dependability requirements. SDRL extends IM-SPDL with the possibility to express impulse- and state reward measures.\ud The logic is interpreted over extended action-based Markov reward model (EMRM), i.e. transition systems containing both immediate and Markovian transitions, where additionally the states and transitions can be enriched with rewards.\ud We define ne the syntax and semantics of the new logic and show that SDRL provides powerful means to specify path-based properties with timing and reward-based restrictions.\ud In general, paths can be characterised by regular expressions, also called programs, where the executability of a program may depend on the validity of test formulae. For the model checking of SDRL time- and reward-bounded path formulae, a deterministic program automaton is constructed from the requirement. Afterwards the product transition\ud system between this automaton and the EMRM is built and subsequently transformed into a continuous time Markov reward model (MRM) on which numerical\ud analysis is performed.\u

Naturalizing Intuition: A Cognitive Science Approach to Moral Cognitions

I argue for a naturalized conception of the faculty of intuition with particular interest in intuition\u27s role in moral contexts. I examine intuition in philosophical discourse: namely, the Classic Intuitionists G.E. Moore, W.D. Ross, and H.A. Prichard. I bring to light relevant distinctions among their conceptions of intuition. The explanation of an intuitive faculty in their philosophy has come to stand for the paradigm of intuition in moral philosophy. In the section following, I will present the objections that call into question intuition. I draw from Robert Audi and Laurence BonJour since their respective projects attempt to deal with these same objections in an attempt to formulate respective Moderate Intuitionist positions. I show how these objections raised against intuitionism are objections to the epistemological role of intuition. After, examining the objections, I present Mediocre Intuitionism and Moderate Intuitionism both of which attempt to rearticulate the use of intuition in moral thinking in ways that are less objectionable. I argue that all these conceptions of intuition are moot, inadequate or incomplete. Finally, I examine research in cognitive science related to intuition and its bearing on the development a complete and adequate conception of intuition. Empirical study of cognition illuminates how conscious and unconscious processes manifest themselves as an intuition. Surprisingly, a relatively consistent picture of intuition can be derived from various empirical studies. Cognitive science will be able to tell us something about the immediacy of intuition, whether intuition is indeed non-inferential, and about the self-evidence of intuition. In particular, the results from empirical studies of intuition affect Moderate Intuitionists\u27 reformulation of intuition. These analyses point to a naturalized conception of intuition

Model Checking Markov Chains with Actions and State Labels

In the past, logics of several kinds have been proposed for reasoning about discrete- or continuous-time Markov chains. Most of these logics rely on either state labels (atomic propositions) or on transition labels (actions). However, in several applications it is useful to reason about both state-properties and action-sequences. For this purpose, we introduce the logic asCSL which provides powerful means to characterize execution paths of Markov chains with actions and state labels. asCSL can be regarded as an extension of the purely state-based logic asCSL (continuous stochastic logic). \ud In asCSL, path properties are characterized by regular expressions over actions and state-formulas. Thus, the truth value of path-formulas does not only depend on the available actions in a given time interval, but also on the validity of certain state formulas in intermediate states.\ud We compare the expressive power of CSL and asCSL and show that even the state-based fragment of asCSL is strictly more expressive than CSL if time intervals starting at zero are employed. Using an automaton-based technique, an asCSL formula and a Markov chain with actions and state labels are combined into a product Markov chain. For time intervals starting at zero we establish a reduction of the model checking problem for asCSL to CSL model checking on this product Markov chain. The usefulness of our approach is illustrated by through an elaborate model of a scalable cellular communication system for which several properties are formalized by means of asCSL-formulas, and checked using the new procedure

Distributed Markovian Bisimulation Reduction aimed at CSL Model Checking

The verification of quantitative aspects like performance and dependability by means of model checking has become an important and vivid area of research over the past decade.\ud \ud An important result of that research is the logic CSL (continuous stochastic logic) and its corresponding model checking algorithms. The evaluation of properties expressed in CSL makes it necessary to solve large systems of linear (differential) equations, usually by means of numerical analysis. Both the inherent time and space complexity of the numerical algorithms make it practically infeasible to model check systems with more than 100 million states, whereas realistic system models may have billions of states.\ud \ud To overcome this severe restriction, it is important to be able to replace the original state space with a probabilistically equivalent, but smaller one. The most prominent equivalence relation is bisimulation, for which also a stochastic variant exists (Markovian bisimulation). In many cases, this bisimulation allows for a substantial reduction of the state space size. But, these savings in space come at the cost of an increased time complexity. Therefore in this paper a new distributed signature-based algorithm for the computation of the bisimulation quotient of a given state space is introduced.\ud \ud To demonstrate the feasibility of our approach in both a sequential, and more important, in a distributed setting, we have performed a number of case studies

The X-ray Properties of M101 ULX-1 = CXOKM101 J140332.74+542102

We report our analysis of X-ray data on M101 ULX-1, concentrating on high state Chandra and XMM-Newton observations. We find that the high state of M101 ULX-1 may have a preferred recurrence timescale. If so, the underlying clock may have periods around 160 or 190 days, or possibly around 45 days. Its short-term variations resemble those of X-ray binaries at high accretion rate. If this analogy is correct, we infer that the accretor is a 20-40 Msun object. This is consistent with our spectral analysis of the high state spectra of M101 ULX-1, from which we find no evidence for an extreme (> 10^40 ergs/s) luminosity. We present our interpretation in the framework of a high mass X-ray binary system consisting of a B supergiant mass donor and a large stellar-mass black hole.Comment: 23 pages, 7 figures, accepted for publication in the Astrophysical Journa

Rich Interfaces for Dependability: Compositional Methods for Dynamic Fault Trees and Arcade models

This paper discusses two behavioural interfaces for reliability analysis: dynamic fault trees, which model the system reliability in terms of the reliability of its components and Arcade, which models the system reliability at an architectural level. For both formalisms, the reliability is analyzed by transforming the DFT or Arcade model to a set of input-output Markov Chains. By using compositional aggregation techniques based on weak bisimilarity, significant reductions in the state space can be obtained