3 Search Results for "Neumann, Frank"


Document
The Standard Model for Programming Languages: The Birth of a Mathematical Theory of Computation

Authors: Simone Martini

Published in: OASIcs, Volume 86, Recent Developments in the Design and Implementation of Programming Languages (2020)


Abstract
Despite the insight of some of the pioneers (Turing, von Neumann, Curry, Böhm), programming the early computers was a matter of fiddling with small architecture-dependent details. Only in the sixties some form of "mathematical program development" will be in the agenda of some of the most influential players of that time. A "Mathematical Theory of Computation" is the name chosen by John McCarthy for his approach, which uses a class of recursively computable functions as an (extensional) model of a class of programs. It is the beginning of that grand endeavour to present programming as a mathematical activity, and reasoning on programs as a form of mathematical logic. An important part of this process is the standard model of programming languages - the informal assumption that the meaning of programs should be understood on an abstract machine with unbounded resources, and with true arithmetic. We present some crucial moments of this story, concluding with the emergence, in the seventies, of the need of more "intensional" semantics, like the sequential algorithms on concrete data structures. The paper is a small step of a larger project - reflecting and tracing the interaction between mathematical logic and programming (languages), identifying some of the driving forces of this process. to Maurizio Gabbrielli, on his 60th birthday

Cite as

Simone Martini. The Standard Model for Programming Languages: The Birth of a Mathematical Theory of Computation. In Recent Developments in the Design and Implementation of Programming Languages. Open Access Series in Informatics (OASIcs), Volume 86, pp. 8:1-8:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{martini:OASIcs.Gabbrielli.8,
  author =	{Martini, Simone},
  title =	{{The Standard Model for Programming Languages: The Birth of a Mathematical Theory of Computation}},
  booktitle =	{Recent Developments in the Design and Implementation of Programming Languages},
  pages =	{8:1--8:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-171-9},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{86},
  editor =	{de Boer, Frank S. and Mauro, Jacopo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.Gabbrielli.8},
  URN =		{urn:nbn:de:0030-drops-132307},
  doi =		{10.4230/OASIcs.Gabbrielli.8},
  annote =	{Keywords: Semantics of programming languages, history of programming languages, mathematical theory of computation}
}
Document
Automated Algorithm Selection and Configuration (Dagstuhl Seminar 16412)

Authors: Holger H. Hoos, Frank Neumann, and Heike Trautmann

Published in: Dagstuhl Reports, Volume 6, Issue 10 (2017)


Abstract
This report documents the programme and the outcomes of Dagstuhl Seminar 16412 "Automated Algorithm Selection and Configuration", which was held October 9--14, 2016 and attended by 34 experts from 10 countries. Research on automated algorithm selection and configuration has lead to some of the most impressive successes within the broader area of empirical algorithmics, and has proven to be highly relevant to industrial applications. Specifically, high-performance algorithms for cnp-hard problems, such as propositional satisfiability (SAT) and mixed integer programming (MIP), are known to have a huge impact on sectors such as manufacturing, logistics, healthcare, finance, agriculture and energy systems, and algorithm selection and configuration techniques have been demonstrated to achieve substantial improvements in the performance of solvers for these problems. Apart from creating synergy through close interaction between the world's leading groups in the area, the seminar pursued two major goals: to promote and develop deeper understanding of the behaviour of algorithm selection and configuration techniques and to lay the groundwork for further improving their efficacy. Towards these ends, the organisation team brought together a group of carefully chosen researchers with strong expertise in computer science, statistics, mathematics, economics and engineering; a particular emphasis was placed on bringing together theorists, empiricists and experts from various application areas, with the goal of closing the gap between theory and practice.

Cite as

Holger H. Hoos, Frank Neumann, and Heike Trautmann. Automated Algorithm Selection and Configuration (Dagstuhl Seminar 16412). In Dagstuhl Reports, Volume 6, Issue 10, pp. 33-74, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


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@Article{hoos_et_al:DagRep.6.10.33,
  author =	{Hoos, Holger H. and Neumann, Frank and Trautmann, Heike},
  title =	{{Automated Algorithm Selection and Configuration (Dagstuhl Seminar 16412)}},
  pages =	{33--74},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2017},
  volume =	{6},
  number =	{10},
  editor =	{Hoos, Holger H. and Neumann, Frank and Trautmann, Heike},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.6.10.33},
  URN =		{urn:nbn:de:0030-drops-69569},
  doi =		{10.4230/DagRep.6.10.33},
  annote =	{Keywords: algorithm configuration, algorithm selection, features, machine learning, optimisation, performance prediction}
}
Document
Runtime Analysis of a Simple Ant Colony Optimization Algorithm

Authors: Frank Neumann and Carsten Witt

Published in: Dagstuhl Seminar Proceedings, Volume 6061, Theory of Evolutionary Algorithms (2006)


Abstract
Ant Colony Optimization (ACO) has become quite popular in recent years. In contrast to many successful applications, the theoretical foundation of this randomized search heuristic is rather weak. Building up such a theory is demanded to understand how these heuristics work as well as to come up with better algorithms for certain problems. Up to now, only convergence results have been achieved showing that optimal solutions can be obtained in a finite amount of time. We present the first runtime analysis of a simple ACO algorithm that transfers many rigorous results with respect to the expected runtime of a simple evolutionary algorithm to our algorithm. In addition, we examine the choice of the evaporation factor, which is a crucial parameter in such an algorithm, in greater detail and analyze its effect with respect to the runtime.

Cite as

Frank Neumann and Carsten Witt. Runtime Analysis of a Simple Ant Colony Optimization Algorithm. In Theory of Evolutionary Algorithms. Dagstuhl Seminar Proceedings, Volume 6061, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)


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@InProceedings{neumann_et_al:DagSemProc.06061.8,
  author =	{Neumann, Frank and Witt, Carsten},
  title =	{{Runtime Analysis of  a Simple Ant Colony Optimization Algorithm}},
  booktitle =	{Theory of Evolutionary Algorithms},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6061},
  editor =	{Dirk V. Arnold and Thomas Jansen and Michael D. Vose and Jonathan E. Rowe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.06061.8},
  URN =		{urn:nbn:de:0030-drops-5928},
  doi =		{10.4230/DagSemProc.06061.8},
  annote =	{Keywords: Randomized Search Heuristics, Ant Colony Optimization, Runtime Analysis}
}
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