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\refsection{0}
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      \field{journaltitle}{Intelligenza Artificiale}
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      \field{title}{cplint on SWISH: Probabilistic logical inference with a web browser}
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      \field{journaltitle}{Theory and Practice of Logic Programming}
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      \field{title}{Probabilistic reasoning with {A}nswer {S}ets}
      \field{volume}{9}
      \field{year}{2009}
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      \field{abstract}{Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast and questions notions generally held to be “laws of nature" by practitioners of numerical computing: \beginlist \item High-level dynamic programs have to be slow. \item One must prototype in one language and then rewrite in another language for speed or deployment. \item There are parts of a system appropriate for the programmer, and other parts that are best left untouched as they have been built by the experts. \endlist We introduce the Julia programming language and its design---a dance between specialization and abstraction. Specialization allows for custom treatment. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Abstraction, which is what good computation is really about, recognizes what remains the same after differences are stripped away. Abstractions in mathematics are captured as code through another technique from computer science, generic programming. Julia shows that one can achieve machine performance without sacrificing human convenience.}
      \field{journaltitle}{SIAM Review}
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      \field{abstract}{DataFrames.jl is a package written for and in the Julia language offering flexible and efficient handling of tabular data sets in memory. Thanks to Julia’s unique strengths, it provides an appealing set of features: Rich support for standard data processing tasks and excellent flexibility and efficiency for more advanced and non-standard operations. We present the fundamental design of the package and how it compares with implementations of data frames in other languages, its main features, performance, and possible extensions. We conclude with a practical illustration of typical data processing operations.}
      \field{journaltitle}{Journal of Statistical Software}
      \field{number}{4}
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      \field{volume}{107}
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      \field{abstract}{The idea of answer set programming is to represent a given computational problem by a logic program whose answer sets correspond to solutions, and then use an answer set solver, such as smodels or dlv, to find an answer set for this program. Applications of this method to planning are related to the line of research on the frame problem that started with the invention of formal nonmonotonic reasoning in 1980.}
      \field{issn}{0004-3702}
      \field{journaltitle}{Artificial Intelligence}
      \field{number}{1}
      \field{title}{Answer set programming and plan generation}
      \field{volume}{138}
      \field{year}{2002}
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      \keyw{Answer sets,Default logic,Frame problem,Logic programming,Planning}
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      \field{journaltitle}{Theory and Practice of Logic Programming}
      \field{number}{6}
      \field{title}{Solution enumeration by optimality in {A}nswer {S}et {P}rogramming}
      \field{volume}{21}
      \field{year}{2021}
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      \list{publisher}{1}{%
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\endrefsection
\endinput

