Workbook for Mastering Game Theory
This workbook presents a structured set of exercises designed to help readers develop a clear, step-by-step understanding of the theories introduced in Mastering Game Theory: A Comprehensive Introduction to Strategic Decision Making (hereafter referred to as the 'main book').
Each chapter mirrors a corresponding chapter in the main book and includes multiple exercises with sample solutions. We distinguish between two types of exercise. The first type consists of true/false statements that help to sharpen intuition and identify common misconceptions, with concise explanations provided at the end of each section. The second type comprises analytical problems requiring deeper reasoning and formal analysis. Some of these problems build on those in the main book, while others are entirely original. Each section concludes with sample solutions reflecting the authors' approach.
Like the main book, this workbook is intended for advanced undergraduate or graduate-level one-semester courses in game theory across economics, mathematics and engineering.
Ismail Saglam earned his BSc in Electrical Engineering and his MA and PhD in Economics from Bilkent University, Turkey. He is currently a Professor of Economics at TOBB University of Economics and Technology (TOBB ETU) in Ankara, Turkey. His research spans a broad range of topics, including applied game theory, axiomatic bargaining, computational economics, matching theory, mechanism design, monetary general equilibrium, noncooperative game theory, oligopoly, operations research, and regulation. He is the author, or a co-author, of many academic journal articles as well as the author of a book, titled "Mastering Game Theory: A Comprehensive Introduction to Strategic Decision Making", published in 2025 by Springer Cham within the Book Series "Classroom Companion: Economics".
Sevval Neva Varol is currently pursuing an M.Sc. in Neuroscience at Bilkent University, Turkey. She holds a B.Sc. in Computer Engineering from TOBB University of Economics and Technology. Her interests center on computer architecture, computational game theory, and the computational foundations of human behavior. She previously conducted research at ETH Zürich's SAFARI Research Group, focusing on processing-in-storage architectures and emerging memory systems, and was a member of award-winning processor design teams. Her experience includes designing RISC-V processors, cache systems, and hardware-level optimizations. More broadly, she explores how complex computational systems, both artificial and biological, give rise to intelligence and behavior across different levels of abstraction.