Delftse Foundations of Computation - 2nd Edition

Stefan Hugtenburg; Neil Yorke-Smith

doi:10.5074/T.2022.005

Delftse Foundations of Computation - 2nd Edition

Authors

Stefan Hugtenburg

Computer Science & Engineering Teaching Team, Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology, The Netherlands

Neil Yorke-Smith

Socio-Technical Algorithmic Research (STAR) Lab, Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology, The Netherlands

https://orcid.org/0000-0002-1814-3515

DOI: https://doi.org/10.5074/T.2022.005

Keywords: propositional logic, predicate logic, proof techniques, naive set theory, theoretical computer science

Synopsis

Delftse Foundations of Computation is a textbook for a one quarter introductory course in theoretical computer science. It includes topics from propositional and predicate logic, proof techniques, set theory and the theory of computation, along with practical applications to computer science. It has no prerequisites other than a general familiarity with computer programming.

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Author Biographies

Stefan Hugtenburg, Computer Science & Engineering Teaching Team, Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology, The Netherlands

Stefan Hugtenburg holds a MSc in Computer Science from the Delft University of Technology, where he now teaches in the undergraduate Computer Science and Engineering programme. He is involved in all courses of the Algorithmics track in the curriculum, starting with this book and the course Reasoning & Logic, up until the final year course Complexity Theory.

Neil Yorke-Smith, Socio-Technical Algorithmic Research (STAR) Lab, Faculty of Electrical Engineering, Mathematics & Computer Science, Delft University of Technology, The Netherlands

Neil Yorke-Smith is an Associate Professor of Algorithmics in the Faculty of Electrical Engineering, Mathematics and Computer Science at the Delft University of Technology. His research focuses on intelligent decision making in complex socio-technical situations, with a particular current interest in agent-based methodologies and behavioural factors in automated planning and scheduling. He teaches Reasoning & Logic and graduate courses in Artificial Intelligence.