171 research outputs found
Foundations of Software Science and Computation Structures
This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.
Foundations of Software Science and Computation Structures
This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.
Foundations of Software Science and Computation Structures
This open access book constitutes the proceedings of the 22nd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2019. The 29 papers presented in this volume were carefully reviewed and selected from 85 submissions. They deal with foundational research with a clear significance for software science
Linguistic probability theory
In recent years probabilistic knowledge-based systems such as Bayesian networks and influence diagrams have come to the fore as a means of representing and reasoning about complex real-world situations. Although some of the
probabilities used in these models may be obtained statistically, where this is
impossible or simply inconvenient, modellers rely on expert knowledge. Experts, however, typically find it difficult to specify exact probabilities and conventional representations cannot reflect any uncertainty they may have. In
this way, the use of conventional point probabilities can damage the accuracy,
robustness and interpretability of acquired models. With these concerns in
mind, psychometric researchers have demonstrated that fuzzy numbers are
good candidates for representing the inherent vagueness of probability estimates, and the fuzzy community has responded with two distinct theories of
fuzzy probabilities.This thesis, however, identifies formal and presentational problems with these
theories which render them unable to represent even very simple scenarios.
This analysis leads to the development of a novel and intuitively appealing
alternative - a
theory of linguistic probabilities patterned after the standard Kolmogorov axioms of probability theory. Since fuzzy numbers lack algebraic
inverses, the resulting theory is weaker than, but generalises its classical counterpart. Nevertheless, it is demonstrated that analogues for classical probabilistic concepts such as conditional probability and random variables can be
constructed. In the classical theory, representation theorems mean that most of
the time the distinction between mass/density distributions and probability
measures can be ignored. Similar results are proven for linguistic probabiliities.From these results it is shown that directed acyclic graphs annotated with linguistic probabilities (under certain identified conditions) represent systems of
linguistic random variables. It is then demonstrated these linguistic Bayesian
networks can utilise adapted best-of-breed Bayesian network algorithms (junction tree based inference and Bayes' ball irrelevancy calculation). These algorithms are implemented in ARBOR, an interactive design, editing and querying
tool for linguistic Bayesian networks.To explore the applications of these techniques, a realistic example drawn from
the domain of forensic statistics is developed. In this domain the knowledge
engineering problems cited above are especially pronounced and expert estimates are commonplace. Moreover, robust conclusions are of unusually critical importance. An analysis of the resulting linguistic Bayesian network for
assessing evidential support in glass-transfer scenarios highlights the potential
utility of the approach
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