Logics for Computer Science

Professor Anita Wasilewska has been teaching a "logic for computer science" class for many years, using presentation slides for ease of comprehension. She earned her Master Degree in Computer Science and Ph.D. in Mathematics from Warsaw University, where she consequently was a faculty of the Mathematics Department from 1967 to 1983. She came to the United States in 1980 as a visiting Assistant Professor in Mathematics at Wesleyan and Yale Universities in Connecticut, before joining Stony Brook’s Department of Computer Science in 1986.She has also published papers, books, and edited books in many domains ranging from Classical and Non-Classical Logics, Automated Theorem Proving, Formal Languages, Theory of Programs, Foundations of Rough Sets in which she was one of the pioneers, to generalized Fuzzy and Rough sets, and Machine Learning.

“This textbook is intended to serve as a first introduction to logic for undergraduate students, especially for those majoring in computer science or a related field. … The text is very reader-friendly, with plenty of explanations. … The problems will provide readers with ample opportunity to hone their skills.” (Katalin Bimbó, Mathematical Reviews, October, 2019)

• 1: Introduction: Paradoxes and Puzzles.- 2: Introduction to Classical Logic.- 3: Propositional Semantics: Classical and Many Valued.- 4: General Proof Systems: Syntax and Semantics.- 5: Hilbert Proof Systems: Deduction and Completeness Theorems for Classical Propositional Logic.- 6: Automated Proof Systems.- 7: Introduction to Intuitionistic and Modal Logics.- 8: Classical Predicate Semantics and Proof Systems.- 9: Completeness and Deduction Theorems for Classical Predicate Logic.- 10: Predicate Automated Proof Systems.- 11: Formal Theories and Godel Theorems.