Meta-Programming in Logic: Third International Workshop, by Peter Gärdenfors (auth.), A. Pettorossi (eds.)

By Peter Gärdenfors (auth.), A. Pettorossi (eds.)

This quantity includes lectures and papers added at Meta ninety two, the 3rd foreign Workshop on Metaprogramming in common sense, held in Uppsala, Sweden,June 1992. the subjects coated contain foundations of metaprogramming in common sense, proposals for metaprogramming languages, concepts for knowledgerepresentation and trust structures, and application transformation and research in good judgment. specific subject matters contain trust revision structures, intensionaldeduction, trust platforms and metaprogramming, ideas of partial deduction, termination in common sense courses, semantics of the "vanilla" metainterpreter, a whole solution process for metaprogramming, semanticsof "demo", hierarchical metalogics, the naming relation in metalevel platforms, modules, reflective brokers, compiler optimizations, metalogic and object-oriented amenities, parallel good judgment languages, using metaprogramming for criminal reasoning, representing gadgets and inheritance, transformation of ordinary courses, negation in immediately generated common sense courses, reordering of literals in deductive databases, summary interpretations, and interarguments in constraint common sense programs.

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Extra info for Meta-Programming in Logic: Third International Workshop, META-92 Uppsala, Sweden, June 10–12, 1992 Proceedings

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Their different stochastic moments can be efficiently computed via BDD-traversal. The main idea of our approach is to limit the explicit exploration and explicit execution of reward functions only to fractions of the low-level MRM, where the missing parts are generated via ZDD manipulations. In contrast to standard methods, this strategy leads to significant runtime-benefits, where the employment of ZDDs yields significant reductions in memory space. Phase 1: Constructing a Symbolic Representation of a CTMC [LS06a]: The main idea of the activity-local state graph generation scheme is the partitioning of the CTMC or the SLTS T to be generated into sets of transitions with label l ∈ Act, where each state is reduced to the activity-dependent markings: T l := {(sdl , l, λ, sdll ) | sdl = χ(SlD , s ) ∧ sdll = χ(SlD , s l ) ∧ (s, l, λ, s l ) ∈ T } (1) During state graph generation the activity-local transitions T l are successively generated, where each is encoded by its own (activity-local) ZDD Zl , which solely depends on the Boolean variables encoding the dependent SVs of activity l.

To appear. 5. Jiˇr´ı Barnat. Distributed Memory LTL Model Checking. PhD thesis, Faculty of Informatics, Masaryk University Brno, 2004. 6. G. Behrmann, T. S. Hune, and F. W. Vaandrager. Distributed Timed Model Checking – How the Search Order Matters. In Proc. Computer Aided Verification, volume 1855 of LNCS, pages 216–231. Springer, 2000. 7. A. Bell and B. R. Haverkort. Sequential and distributed model checking of petri net specifications. Int J Softw Tools Technol Transfer, 7(1):43–60, 2005. 8. S.

C. Corbett. Property Specification Patterns for Finite-State Verification. In Proc. Workshop on Formal Methods in Software Practice, pages 7–15. ACM Press, 1998. 34 L. Brim 19. S. Edelkamp and S. Jabbar. Large-Scale Directed Model Checking LTL. In Model Checking Software: 13th International SPIN Workshop, volume 3925 of LNCS, pages 1–18. Springer-Verlag, 2006. 20. K. Fisler, R. Fraer, G. Kamhi, M. Y. Vardi, and Z. Yang. Is there a best symbolic cycle-detection algorithm? In Proc. Tools and Algorithms for the Construction and Analysis of Systems, volume 2031 of LNCS, pages 420–434.

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