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Based on the Kripke structure, linear temporal logic and generalized possibility measure, this article studies the model checking problems of generalized possibilistic fuzzy linear temporal logic (GPoFTL). The generalized possibilistic Kripke structure is introduced to describe the system model. The syntax of GPoFTL, which includes fuzzy temporal operators such as ''soon'', ''presently'', ''gradually'', ''within'', ''last'', ''nearly always'', ''almost alwayss'', ''in the long distant future'', ''in the middle of'', ''nearly until'' and ''almost until'', and its language semantics and path semantics under generalized possibility measure are given. Next, we explain the semantics of fuzzy temporal operators through some examples and prove that GPoFTL is an extension of generalized possibilistic linear temporal logic in fuzzy time temporal logic. Furthermore, the GPoFTL model checking algorithm is given by explicit calculation formulas one by one for any GPoFTL formula involving fuzzy temporal operators using fuzzy matrix operations. Last, the algorithm of necessary threshold model checking of GPoFTL is studied using automata theory and its time complexity is discussed. [ABSTRACT FROM AUTHOR]

Open pNets are formal models that can express the behaviour of open systems, either synchronous, asynchronous, or heterogeneous. They are endowed with a symbolic operational semantics in terms of open automata, which allows us to check properties of such systems in a compositional manner. We present an algorithm computing these semantics, building predicates expressing the synchronisation conditions between the events of pNet sub-systems. Checking such predicates requires symbolic reasoning about first order logics and application-specific data. We use the Z3 SMT engine to check satisfiability of the predicates. We also propose and implement an optimised algorithm that performs part of the pruning on the fly, and show its correctness with respect to the original one. We illustrate the approach using two use-cases: the first one is a classical process-algebra operator for which we provide several encodings, and prove some basic properties. The second one is industry-oriented and based on the so-called "BIP architectures", which have been used to specify the control software of a nanosatellite at the EPFL Space Engineering Center. We use pNets to encode a BIP architecture extended with explicit data, compute its semantics and discuss its properties, and then show how our algorithms scale up, using a composition of two such architectures. [ABSTRACT FROM AUTHOR]

The role of logic in mathematics education has been widely discussed from the seventies and eighties during the "modern maths period" till now, and remains still a rather controversial issue in the international community. Nevertheless, the relevance of discrete mathematics and algorithmic thinking for the development of heuristic and logical competences is both one of the main points of the program of Tamás Varga, and of some didactic teams in France. In this paper, we first present the semantic perspective in mathematics education and the role of logic in the Hungarian tradition. Then, we present insights on the role of research problems in the French tradition. Finely, we raise some didactical issues in algorithmic thinking at the interface of mathematics and computer science. [ABSTRACT FROM AUTHOR]

In Temporal Logic (TL), a well-formed formula is generally formed by applying rules of its syntax finitely many times. However, under some circumstances, although formulas such as ones expressed by index set expressions , are constructed via applying rules of the syntax infinitely many times, they are possibly still well-formed since their equivalent concise syntax formulas can be found. With this motivation, this paper investigates the relationship between formulas specified by index set expressions and concise syntax by means of fixed-point approach. Firstly, we present two kinds of formulas, namely ⋁ i ∈ N 0 ◯ i Q and ⋁ i ∈ N 0 Q i , and prove they are indeed well-formed by proving they are equivalent to formulas ◇ Q and Q ⁎ respectively. Further, we generalize ⋁ i ∈ N 0 ◯ i Q to ⋁ i ∈ N 0 P (i) ∧ ◯ i Q and explore the least and greatest fixed-points of an abstract equation X ≡ Q ∨ P ∧ ◯ X. Based on these, some well-formed special instances of ⋁ i ∈ N 0 P (i) ∧ ◯ i Q are obtained. Besides, with the index set expression technique, we equivalently represent ' U ' (strong until) and ' W ' (weak until) constructs of propositional Linear Temporal Logic (LTL) within Propositional Projection Temporal Logic (PPTL). [ABSTRACT FROM AUTHOR]

Objective: Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones.Methods: Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types.Material: This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies.Results: The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems.Conclusion: Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. [ABSTRACT FROM AUTHOR]

Quantified CTL (QCTL) extends the temporal logic CTL with quantifications over atomic propositions. This extension is known to be very expressive: QCTL allows us to express complex properties over Kripke structures (it is as expressive as MSO). Several semantics exist for the quantifications: here, we work with the structure semantics , where the extra propositions label the Kripke structure (and not its execution tree), and the model-checking problem is known to be PSPACE -complete in this framework. We propose a new model-checking algorithm for QCTL based on a reduction to QBF. We consider several reduction strategies and we compare them with a prototype (based on several QBF solvers) on different examples. [ABSTRACT FROM AUTHOR]

We develop a game-theoretic semantics (GTS) for the fragment AT L + of the alternating-time temporal logic AT L ⁎ , thereby extending the recently introduced GTS for ATL. We show that the game-theoretic semantics is equivalent to the standard compositional semantics of AT L + with perfect-recall strategies. Based on the new semantics, we provide an analysis of the memory and time resources needed for model checking AT L + and show that strategies of the verifier that use only a very limited amount of memory suffice. Furthermore, using the GTS , we provide a new algorithm for model checking AT L + and identify a natural hierarchy of tractable fragments of AT L + that substantially extend ATL. [ABSTRACT FROM AUTHOR]