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Título : Algorithms and Programming : Problems and Solutions Tipo de documento: documento electrónico Autores: Shen, Alexander ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2010 Otro editor: Imprint: Springer Colección: Springer Undergraduate Texts in Mathematics and Technology, ISSN 1867-5506 Número de páginas: XII, 272 p Il.: online resource ISBN/ISSN/DL: 978-1-4419-1748-5 Idioma : Inglés (eng) Palabras clave: Mathematics Computer programming Algorithms mathematics Numerical analysis Analysis Programming Techniques Computational and Algorithm Problem Complexity Clasificación: 51 Matemáticas Resumen: "Algorithms and Programming" is primarily intended for a first year undergraduate course in programming. Structured in a problem-solution format, the text motivates the student to think through the programming process, thus developing a firm understanding of the underlying theory. Although a moderate familiarity with programming is assumed, the book is easily utilized by students new to computer science. The more advanced chapters make the book useful for a graduate course in the analysis of algorithms and/or compiler construction. New to the second edition are added chapters on suffix trees, games and strategies, and Huffman coding as well as an appendix illustrating the ease of conversion from Pascal to C. The material covers such topics as combinatorics, sorting, searching, queues, grammar and parsing, selected well-known algorithms, and much more. Reviews of the 1st Edition: "The book is addressed both to ambitious students and instructors looking for interesting problems [and] fulfills this task perfectly, especially if the reader has a good mathematical background." — Zentralblatt MATH "This book is intended for students, engineers, and other people who want to improve their computer skills.... The chapters can be read independently. Throughout the book, useful exercises give readers a feeling for how to apply the theory." — Computing Reviews "Overall...the book is well done. I recommend it to teachers and those wishing to sharpen their data structure and compiler skills." — SIGACT News Nota de contenido: Variables, expressions, assignments -- Generation of combinatorial objects -- Tree traversal (backtracking) -- Sorting -- Finite-state algorithms in text processing -- Data types -- Recursion -- Recursive and non-recursive programs -- Graph algorithms -- Pattern matching -- Games analysis -- Optimal coding -- Set representation. Hashing -- Sets, trees, and balanced trees -- Context-free grammars -- Left-to-right parsing (LR) En línea: http://dx.doi.org/10.1007/978-1-4419-1748-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33609 Algorithms and Programming : Problems and Solutions [documento electrónico] / Shen, Alexander ; SpringerLink (Online service) . - New York, NY : Springer New York : Imprint: Springer, 2010 . - XII, 272 p : online resource. - (Springer Undergraduate Texts in Mathematics and Technology, ISSN 1867-5506) .
ISBN : 978-1-4419-1748-5
Idioma : Inglés (eng)
Palabras clave: Mathematics Computer programming Algorithms mathematics Numerical analysis Analysis Programming Techniques Computational and Algorithm Problem Complexity Clasificación: 51 Matemáticas Resumen: "Algorithms and Programming" is primarily intended for a first year undergraduate course in programming. Structured in a problem-solution format, the text motivates the student to think through the programming process, thus developing a firm understanding of the underlying theory. Although a moderate familiarity with programming is assumed, the book is easily utilized by students new to computer science. The more advanced chapters make the book useful for a graduate course in the analysis of algorithms and/or compiler construction. New to the second edition are added chapters on suffix trees, games and strategies, and Huffman coding as well as an appendix illustrating the ease of conversion from Pascal to C. The material covers such topics as combinatorics, sorting, searching, queues, grammar and parsing, selected well-known algorithms, and much more. Reviews of the 1st Edition: "The book is addressed both to ambitious students and instructors looking for interesting problems [and] fulfills this task perfectly, especially if the reader has a good mathematical background." — Zentralblatt MATH "This book is intended for students, engineers, and other people who want to improve their computer skills.... The chapters can be read independently. Throughout the book, useful exercises give readers a feeling for how to apply the theory." — Computing Reviews "Overall...the book is well done. I recommend it to teachers and those wishing to sharpen their data structure and compiler skills." — SIGACT News Nota de contenido: Variables, expressions, assignments -- Generation of combinatorial objects -- Tree traversal (backtracking) -- Sorting -- Finite-state algorithms in text processing -- Data types -- Recursion -- Recursive and non-recursive programs -- Graph algorithms -- Pattern matching -- Games analysis -- Optimal coding -- Set representation. Hashing -- Sets, trees, and balanced trees -- Context-free grammars -- Left-to-right parsing (LR) En línea: http://dx.doi.org/10.1007/978-1-4419-1748-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33609 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Hans Petter Langtangen ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXXII, 798 p. 79 illus., 30 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-642-30293-0 Idioma : Inglés (eng) Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. Nota de contenido: Preface -- Computing with Formulas -- Loops and Lists -- Functions and Branching -- User Input and Error Handling -- Array Computing and Curve Plotting -- Dictionaries and Strings -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus -- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Migrating Python to Compiled Code -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-30293-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32988 A Primer on Scientific Programming with Python [documento electrónico] / Hans Petter Langtangen ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012 . - XXXII, 798 p. 79 illus., 30 illus. in color : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-30293-0
Idioma : Inglés (eng)
Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. Nota de contenido: Preface -- Computing with Formulas -- Loops and Lists -- Functions and Branching -- User Input and Error Handling -- Array Computing and Curve Plotting -- Dictionaries and Strings -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus -- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Migrating Python to Compiled Code -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-30293-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32988 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Hans Petter Langtangen ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXX, 706 p. 72 illus., 28 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-642-18366-9 Idioma : Inglés (eng) Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science Nota de contenido: Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-18366-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33411 A Primer on Scientific Programming with Python [documento electrónico] / Hans Petter Langtangen ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - XXX, 706 p. 72 illus., 28 illus. in color : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-18366-9
Idioma : Inglés (eng)
Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science Nota de contenido: Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-18366-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33411 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Hans Petter Langtangen ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2009 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXVIII, 694 p Il.: online resource ISBN/ISSN/DL: 978-3-642-02475-7 Idioma : Inglés (eng) Palabras clave: Computer science Software engineering programming Mathematics mathematics Physics Science of Computing Computational and Engineering Programming Techniques Engineering/Programming Operating Systems Numerical Clasificación: 51 Matemáticas Resumen: Theaimofthisbookistoteachcomputerprogrammingusingexamples from mathematics and the natural sciences. We have chosen to use the Python programming language because it combines remarkable power with very clean, simple, and compact syntax. Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to Matlab and a good language for doing mathematical computing. It is easy to combine Python with compiled languages, like Fortran, C, and C++, which are widely used languages forscienti?ccomputations.AseamlessintegrationofPythonwithJava is o?ered by a special version of Python called Jython. The examples in this book integrate programming with appli- tions to mathematics, physics, biology, and ?nance. The reader is - pected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an - vantage to take a university calculus course in parallel, preferably c- taining both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful Nota de contenido: Computing with Formulas -- Basic Constructions -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Sequences and Difference Equations -- Files, Strings, and Dictionaries -- to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming En línea: http://dx.doi.org/10.1007/978-3-642-02475-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34071 A Primer on Scientific Programming with Python [documento electrónico] / Hans Petter Langtangen ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2009 . - XXVIII, 694 p : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-02475-7
Idioma : Inglés (eng)
Palabras clave: Computer science Software engineering programming Mathematics mathematics Physics Science of Computing Computational and Engineering Programming Techniques Engineering/Programming Operating Systems Numerical Clasificación: 51 Matemáticas Resumen: Theaimofthisbookistoteachcomputerprogrammingusingexamples from mathematics and the natural sciences. We have chosen to use the Python programming language because it combines remarkable power with very clean, simple, and compact syntax. Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to Matlab and a good language for doing mathematical computing. It is easy to combine Python with compiled languages, like Fortran, C, and C++, which are widely used languages forscienti?ccomputations.AseamlessintegrationofPythonwithJava is o?ered by a special version of Python called Jython. The examples in this book integrate programming with appli- tions to mathematics, physics, biology, and ?nance. The reader is - pected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an - vantage to take a university calculus course in parallel, preferably c- taining both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful Nota de contenido: Computing with Formulas -- Basic Constructions -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Sequences and Difference Equations -- Files, Strings, and Dictionaries -- to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming En línea: http://dx.doi.org/10.1007/978-3-642-02475-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34071 Ejemplares
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Título : Reasoning Robots : The Art and Science of Programming Robotic Agents Tipo de documento: documento electrónico Autores: Thielscher, Michael ; SpringerLink (Online service) Editorial: Dordrecht : Springer Netherlands Fecha de publicación: 2005 Colección: Applied Logic Series, ISSN 1386-2790 num. 33 Número de páginas: XIV, 328 p Il.: online resource ISBN/ISSN/DL: 978-1-4020-3069-7 Idioma : Inglés (eng) Palabras clave: Philosophy Computer programming Artificial intelligence of Technology Programming Techniques Intelligence (incl. Robotics) Clasificación: 51 Matemáticas Resumen: The book provides an in-depth and uniform treatment of a mathematical model for reasoning robotic agents. The book also contains an introduction to a programming method and system based on this model. The mathematical model, known as the "Fluent Calculus,'' describes how to use classical first-order logic to set up symbolic models of dynamic worlds and to represent knowledge of actions and their effects. Robotic agents use this knowledge and their reasoning facilities to make decisions when following high-level, long-term strategies. The book covers the issues of reasoning about sensor input, acting under incomplete knowledge and uncertainty, planning, intelligent troubleshooting, and many other topics. The mathematical model is supplemented by a programming method which allows readers to design their own reasoning robotic agents. The usage of this method, called "FLUX,'' is illustrated by many example programs. The book includes the details of an implementation of FLUX using the standard programming language PROLOG, which allows readers to re-implement or to modify and extend the generic system. The design of autonomous agents, including robots, is one of the most exciting and challenging goals of Artificial Intelligence. Reasoning robotic agents constitute a link between knowledge representation and reasoning on the one hand, and agent programming and robot control on the other. The book provides a uniform mathematical model for the problem-driven, top-down design of rational agents, which use reasoning for decision making, planning, and troubleshooting. The implementation of the mathematical model by a general PROLOG program allows readers to practice the design of reasoning robotic agents. Since all implementation details are given, the generic system can be easily modified and extended Nota de contenido: Special Fluent Calculus -- Special FLUX -- General Fluent Calculus -- General FLUX -- Knowledge Programming -- Planning -- Nondeterminism -- Imprecision* -- Indirect Effects: Ramification Problem* -- Troubleshooting: Qualification Problem -- Robotics En línea: http://dx.doi.org/10.1007/1-4020-3069-X Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35207 Reasoning Robots : The Art and Science of Programming Robotic Agents [documento electrónico] / Thielscher, Michael ; SpringerLink (Online service) . - Dordrecht : Springer Netherlands, 2005 . - XIV, 328 p : online resource. - (Applied Logic Series, ISSN 1386-2790; 33) .
ISBN : 978-1-4020-3069-7
Idioma : Inglés (eng)
Palabras clave: Philosophy Computer programming Artificial intelligence of Technology Programming Techniques Intelligence (incl. Robotics) Clasificación: 51 Matemáticas Resumen: The book provides an in-depth and uniform treatment of a mathematical model for reasoning robotic agents. The book also contains an introduction to a programming method and system based on this model. The mathematical model, known as the "Fluent Calculus,'' describes how to use classical first-order logic to set up symbolic models of dynamic worlds and to represent knowledge of actions and their effects. Robotic agents use this knowledge and their reasoning facilities to make decisions when following high-level, long-term strategies. The book covers the issues of reasoning about sensor input, acting under incomplete knowledge and uncertainty, planning, intelligent troubleshooting, and many other topics. The mathematical model is supplemented by a programming method which allows readers to design their own reasoning robotic agents. The usage of this method, called "FLUX,'' is illustrated by many example programs. The book includes the details of an implementation of FLUX using the standard programming language PROLOG, which allows readers to re-implement or to modify and extend the generic system. The design of autonomous agents, including robots, is one of the most exciting and challenging goals of Artificial Intelligence. Reasoning robotic agents constitute a link between knowledge representation and reasoning on the one hand, and agent programming and robot control on the other. The book provides a uniform mathematical model for the problem-driven, top-down design of rational agents, which use reasoning for decision making, planning, and troubleshooting. The implementation of the mathematical model by a general PROLOG program allows readers to practice the design of reasoning robotic agents. Since all implementation details are given, the generic system can be easily modified and extended Nota de contenido: Special Fluent Calculus -- Special FLUX -- General Fluent Calculus -- General FLUX -- Knowledge Programming -- Planning -- Nondeterminism -- Imprecision* -- Indirect Effects: Ramification Problem* -- Troubleshooting: Qualification Problem -- Robotics En línea: http://dx.doi.org/10.1007/1-4020-3069-X Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35207 Ejemplares
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