Mathematical Logic II
Author: Dag Normann
*Wait a few seconds for the document to load, the time may vary depending on your internet connection. If you prefer, you can download the file by clicking on the link below.
Information
Description: Mathematical Logic II por Dag Normann is a compendium for an advanced course in mathematical logic. It covers classical model theory, finitary model theory, and computability theory, offering a valuable resource for understanding the foundations of mathematics.
Pages: 147
Megabytes: 0.64 MB
This may interest you
Mathematical Logic
Extension: PDF | 119 pages
Mathematical Logic by Lou van den Dries presents lecture notes for Math 570, offering a structured journey into logic's core concepts. It explores logic's theoretical underpinnings and equips students with essential knowledge in mathematical reasoning.
Sentential Logic
Extension: PDF | 259 pages
Sentential Logic by Tony Roy is a valuable resource for grasping mathematical logic, particularly sentential logic. This excerpt offers an accessible introduction to symbolic logic, including classical symbolic logic and Gödel's incompleteness results.
Logic and Set Theory
Extension: PDF | 22 pages
Logic and Set Theory por Henry D Pfister Web Site offers a concise introduction to mathematical logic and set theory. It explores fundamental concepts, providing a solid foundation for understanding rigorous proofs and mathematical reasoning.
Mathematical Logic I
Extension: PDF | 28 pages
Mathematical Logic I by Michael Rathjen offers a foundational introduction to mathematical logic, covering propositional logic, set theory, and mathematical induction. It explores the historical development and modern applications of logic, making it a valuable resource for understanding the principles underlying formal reasoning.
Notes on Mathematical Logic
Extension: PDF | 114 pages
Notes on Mathematical Logic by David W Kueker presents a rigorous treatment of sentential and first-order logic, including completeness and model theory. This PDF provides a solid foundation in logic, essential for understanding the theoretical underpinnings of artificial intelligence.