Course CSE 102 · Year I · Autumn 2022-2023

MATHEMATICAL AND COMPUTATIONAL LOGICS

Compulsory course in Computer Science (in English), taught by Pax Dorin Wainberg-Drăghiciu.

This course page is from 2022-2023 and is archived.
See this course for the current academic year

Overview

Lecturer
Pax Dorin Wainberg-Drăghiciu
Seminar tutor
Pax Dorin Wainberg-Drăghiciu
Type of course
Compulsory
Language of instruction
English
Erasmus language
English
Domain
Computer Science
Field of study
Computer Science (in English)
Form of education
Full-time
Form of instruction
Class
Credit awarded by
Grade
Teaching methods
Lecture, conversation, exemplification.
Entry requirements
-

Aims

The discipline Computational logics aims to provide students opportunities to identify and use knowledge of the laws of human reasoning.

The purposes of mastering proper expertise and especially for their enforcement in the areas of artificial intelligence, analysis and synthesis of logic circuits, the automatic demonstration theorems, the logic programming.

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Course contents

1. Propositional Logic: Logical operations, Logical equivalence of formulas, Duality law 2. Decision Problem. Perfect normal forms. 3. Propositional calculus elements: The concept of formula. True formulas 4. Deduction theorem. Rules of propositional calculus. 5. Logically equivalent formulas. Deductibility theorems. Formulas in propositional algebra and propositional calculus. 6. No contradiction and completeness of propositional calculus. Independence of propositional calculus axioms. 7. Predicate calculus: Definitions of predicates and quantifiers. Normal forms. 8. Predicate calculus formulas and axioms. 9. Noncontradiction and narrowly completeness of predicate calculus. Theorems of predicate calculus. 10. Equivalent formulas in predicate calculus. Axioms of predicate calculus. 11. Numeral: positional representation of numbers, algorithms for crossing a number from one base to another, the four operations in various numeral, numeral 2, 8, 16; characteristic elements. 12. Representation of numerical information in memory computer systems: fixed-point representation of numerical information, floating point representation of numerical information, arithmetic operations with floating point numbers, IEEE P754 Standard 13. Boolean functions and their realization: the notion of Boolean function of several variables, Boolean operations AND, OR, NOT 14. The operation of AND gate, OR gate, NOT gate circuits; Implementation of Boolean functions. Boolean functions applications

Learning outcomes

Acquiring fundamental knowledge concerning the discipline specific concepts: formal systems, judgments and sentences, modal logic elements, probability, predicate logic elements; training in problem solving skills necessary for circuit design and optimization of computer systems based on structural formulas, representing information in memory computer systems.

Assessment

Written paper –70%; continuous assessment – 30%.

Recommended reading

Logical Foundations of Artificial Intelligence
• Michael R. Genesereth, Nils J. Nislsson
Morgan Kaufmann Publishers, -, 1988 · -
Artificial Intelligence. A Modern Approach
• S. Russell and P. Norvig
Prentice Hall, -, 1995 · -
Mathematical Logic
• Stphen G. Simson
Department of Mathematics The Pennsylvania State University, -, - · -