Probabilistic theorem proving
نویسندگان
چکیده
منابع مشابه
Probabilistic Analysis Using Theorem Proving
In this chapter, the authors first provide the overall methodology for the theorem proving formal probabilistic analysis followed by a brief introduction to the HOL4 theorem prover. The main focus of this book is to provide a comprehensive framework for formal probabilistic analysis as an alternative to less accurate techniques like simulation and paper-and-pencil methods and to other less scal...
متن کاملProbabilistic Analysis using Theorem Proving
Traditionally, computer simulation techniques are used to perform probabilistic analysis. However, they provide less accurate results and cannot handle large-scale problems due to their enormous CPU time requirements. Recently, a significant amount of formalization has been done in the HOL theorem prover that allows us to conduct precise probabilistic analysis using theorem proving and thus ove...
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Formal Probabilistic Analysis using Theorem Proving Osman Hasan, Ph.D. Concordia University, 2008 Probabilistic analysis is a tool of fundamental importance to virtually all scientists and engineers as they often have to deal with systems that exhibit random or unpredictable elements. Traditionally, computer simulation techniques are used to perform probabilistic analysis. However, they provide...
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Probabilistic techniques play a major role in the design and analysis of wireless systems as they contain a significant amount of random or unpredictable components. Traditionally, computer simulation techniques are used to perform probabilistic analysis of wireless systems but they provide inaccurate results and usually require enormous amount of CPU time in order to attain reasonable estimate...
متن کاملProbabilistic Theorem Proving: A Unifying Approach for Inference in Probabilistic Programming
Inference is the key bottleneck in probabilistic programming. Often, the main advantages of probabilistic programming – simplicity, modularity, ease-of-use, etc. – are dwarfed by the complexity and intractability of inference. In fact, one of the main reasons for the scarcity/absence of large applications and real-world systems that are based in large part on probabilistic programming languages...
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ژورنال
عنوان ژورنال: Communications of the ACM
سال: 2016
ISSN: 0001-0782,1557-7317
DOI: 10.1145/2936726