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In dit boek worden de bouwstenen van het programmeren in het algemeen en het objectgeoriënteerd programmeren in het bijzonder aangereikt op maat van leerlingen uit de derde graad van het secundair onderwijs. Spelenderwijs verdiepen we ons via de educatieve programmeeromgeving BlueJ in de programmeertaal Java. De controlestructuren, zoals selectie en iteratie, komen pas aan bod wanneer dit nodig is en staan niet los van het objectgeoriënteerd programmeren.In dit handboek vind je naast theoretische achtergrond ook heel veel demo-materiaal. Bovendien volgt na elk bouwsteentje steeds een basisoefening en zijn alle hoofdstukken voorzien van een uitgebreide verzameling herhalingsoefeningen.Leren programmeren is een aanrader voor elke leerling die zich wil voorbereiden op het eerste jaar van een richting informaticawetenschappen in het hoger onderwijs.https://www.acco.be/nl-be/items/9789462927193/Leren-programmeren

Programmeren --- Java (programmeertaal) --- BlueJ --- Logic programming --- Java (Computer program language) --- Handbooks, manuals, etc. --- PXL-IT 2018 --- informatica --- programmeren --- Java --- Secundair onderwijs --- 3e graad secundair onderwijs --- Informatica --- Kind

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This book introduces the notions and methods of formal logic from a computer science standpoint, covering propositional logic, predicate logic, and foundations of logic programming. It presents applications and themes of computer science research such as resolution, automated deduction, and logic programming in a rigorous but readable way. The style and scope of the work, rounded out by the inclusion of exercises, make this an excellent textbook for an advanced undergraduate course in logic for computer scientists. This is a short introductory book on the topic of propositional and first-order logic, with a bias towards computer scientists…. Schöning decides to concentrate on computational issues, and gives us a short book (less than 170 pages) with a tight storyline…. I found this a nicely written book with many examples and exercises (126 of them). The presentation is natural and easy to follow…. This book seems suitable for a short course, a seminar series, or part of a larger course on Prolog and logic programming, probably at the advanced undergraduate level. — SIGACT News Contains examples and 126 interesting exercises which put the student in an active reading mode.... Would provide a good university short course introducing computer science students to theorem proving and logic programming. — Mathematical Reviews This book concentrates on those aspects of mathematical logic which have strong connections with different topics in computer science, especially automated deduction, logic programming, program verification and semantics of programming languages.... The numerous exercises and illustrative examples contribute a great extent to a better understanding of different concepts and results. The book can be successfully used as a handbook for an introductory course in artificial intelligence. — Zentralblatt MATH.

Programming --- Computer science --- Mathematical logic --- Logic, Symbolic and mathematical. --- Logic programming. --- Computer science. --- Mathematical Logic and Formal Languages. --- Mathematical Logic and Foundations. --- Algebra of logic --- Logic, Universal --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Informatics --- Science --- Mathematical logic. --- Logique mathématique --- Programmation logique --- Logique des prédicats

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This volume contains the research papers presented at the 17th International Conference on Logic for Programming, Arti?cial Intelligence, and Reasoning (LPAR-17), held in Yogyakarta, Indonesia, October 10-15, 2010, accompanied by the 8th International Workshop on the Implementation of Logic (IWIL-8, organized by Eugenia Ternovska, Stephan Schulz, and Geo? Sutcli?e) and the 5th International Workshop on Analytic Proof Systems (APS-5, organized by Matthias Baaz and Christian Fermuller ¨ ). The call for papers attracted 133 abstract submissions of which 105 ma- rialized into full submissions, each of which was assigned for reviewing to at least three Program Committee members; 41 papers were accepted after - tense discussions. Once more the EasyChair system provided an ideal platform for submission, reviewing, discussions, and collecting ?nal versions of accepted papers. The program included three invited talks by Krishnendu Chatterjee, Joseph Halpern, and Michael Maher, as well as an invited tutorial by Norbert Preining. They are documented by the corresponding papers and abstract, respectively, in these proceedings, which this year appear for the ?rst time in the ARCoSS subline of the Lecture Notes in Computer Science.

Computer Science. --- Artificial Intelligence (incl. Robotics). --- Software Engineering. --- Logics and Meanings of Programs. --- Mathematical Logic and Formal Languages. --- Programming Techniques. --- Programming Languages, Compilers, Interpreters. --- Computer science. --- Software engineering. --- Logic design. --- Artificial intelligence. --- Informatique --- Génie logiciel --- Structure logique --- Intelligence artificielle --- Artificial intelligence --- Automatic theorem proving --- Logic programming --- 681.3*D24 --- 681.3*F3 --- 681.3*F41 --- 681.3*I23 --- Computer programming --- Automated theorem proving --- Theorem proving, Automated --- Theorem proving, Automatic --- Proof theory --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Program verification: assertion checkers; correctness proofs; reliability; validation (Software engineering)--See also {681.3*F31} --- Logics and meanings of programs (Theory of computation) --- Mathematical logic: computability theory; computational logic; lambda calculus; logic programming; mechanical theorem proving; model theory; proof theory;recursive function theory--See also {681.3*F11}; {681.3*I22}; {681.3*I23} --- Deduction and theorem proving: answer/reason extraction; reasoning; resolution; metatheory; mathematical induction; logic programming (Artificial intelligence) --- 681.3*I23 Deduction and theorem proving: answer/reason extraction; reasoning; resolution; metatheory; mathematical induction; logic programming (Artificial intelligence) --- 681.3*F41 Mathematical logic: computability theory; computational logic; lambda calculus; logic programming; mechanical theorem proving; model theory; proof theory;recursive function theory--See also {681.3*F11}; {681.3*I22}; {681.3*I23} --- 681.3*F3 Logics and meanings of programs (Theory of computation) --- 681.3*D24 Program verification: assertion checkers; correctness proofs; reliability; validation (Software engineering)--See also {681.3*F31}

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This textbook covers logical and relational learning in depth, and hence provides an introduction to inductive logic programming (ILP), multirelational data mining (MRDM) and (statistical) relational learning (SRL). These subfields of data mining and machine learning are concerned with the analysis of complex and structured data sets that arise in numerous applications, such as bio- and chemoinformatics, network analysis, Web mining, natural language processing, within the rich representations offered by relational databases and computational logic. The author introduces the machine learning and representational foundations of the field and explains some important techniques in detail by using some of the classic case studies centered around well-known logical and relational systems. The book is suitable for use in graduate courses and should be of interest to graduate students and researchers in computer science, databases and artificial intelligence, as well as practitioners of data mining and machine learning. It contains numerous figures and exercises, and slides are available for many chapters.

Computer science. --- Software engineering. --- Database management. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Computer Science. --- Software Engineering/Programming and Operating Systems. --- Artificial Intelligence (incl. Robotics). --- Data Mining and Knowledge Discovery. --- Database Management. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Computer software engineering --- Engineering --- Informatics --- Science --- Logic programming. --- Uncertainty (Information theory) --- Machine learning --- Statistical methods. --- Learning, Machine --- Artificial intelligence --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Probabilities --- Questions and answers --- Computer programming --- Information Technology --- Artificial Intelligence --- Data mining --- Logic programming --- Relational databases --- Apprentissage automatique --- Exploration de données (Informatique) --- Programmation logique --- Bases de données relationnelles --- Information storage and retrieva. --- Artificial Intelligence. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Artificial intelligence. Robotics. Simulation. Graphics