Game Theory II: Advanced Applications
Delve into sophisticated game theory principles and their real-world applications through this comprehensive course.
Delve into sophisticated game theory principles and their real-world applications through this comprehensive course.
Delve into the advanced applications of game theory with this course from Stanford University and The University of British Columbia. Building on foundational game theory concepts, this course focuses on designing interactions between agents to achieve optimal social outcomes. You'll explore three main areas: social choice theory, mechanism design, and auction theory. The curriculum covers collective decision-making processes, voting systems, and key theoretical results like Arrow's Theorem. You'll learn about mechanism design for self-interested agents, including the powerful Vickrey-Clarke-Groves mechanisms. The course concludes with an in-depth look at auction theory, from basic concepts to advanced topics like revenue equivalence and optimal auction design. Through lectures, quizzes, and problem sets, you'll gain a deep understanding of how game theory can be applied to real-world scenarios in economics, politics, and business.
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English
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What you'll learn
Understand advanced concepts in social choice theory and voting systems
Analyze the implications of Arrow's Theorem and related impossibility results
Apply mechanism design principles to create effective incentive structures
Explore the Vickrey-Clarke-Groves family of mechanisms and their applications
Compare different auction formats and analyze optimal bidding strategies
Evaluate the revenue equivalence theorem and its implications for auction design
Skills you'll gain
This course includes:
379 Minutes PreRecorded video
20 assignments
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There are 5 modules in this course
This advanced course in game theory focuses on the design of interactions between rational agents to achieve desirable social outcomes. The curriculum is structured around three main topics: social choice theory, mechanism design, and auction theory. In the social choice theory section, students explore collective decision-making processes, voting systems, and key theoretical results such as Arrow's Theorem. The mechanism design portion of the course introduces frameworks for creating systems that incentivize self-interested agents to act in ways that benefit the group, including the powerful family of Vickrey-Clarke-Groves mechanisms. The final section on auction theory covers various auction formats, bidding strategies, and advanced concepts like revenue equivalence and optimal auction design. Throughout the course, students engage with complex theoretical concepts and their practical applications in economics, politics, and business.
Social Choice
Module 1 · 3 Hours to complete
Mechanism Design
Module 2 · 4 Hours to complete
Efficient Mechanisms
Module 3 · 3 Hours to complete
Auctions
Module 4 · 4 Hours to complete
Final Exam
Module 5 · 30 Minutes to complete
Fee Structure
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Instructors
Leading Scholar in Economics and Network Theory
Matthew O. Jackson is the William D. Eberle Professor of Economics at Stanford University, renowned for his contributions to game theory, microeconomic theory, and the analysis of social and economic networks. He is also an external faculty member of the Santa Fe Institute and a senior fellow at CIFAR (the Canadian Institute for Advanced Research). Jackson has authored numerous influential articles and the acclaimed book Social and Economic Networks, which explores the intricate relationships that shape economic interactions. His esteemed career is marked by significant accolades, including membership in the National Academy of Sciences, fellowship in the Econometric Society and the American Academy of Arts and Sciences, as well as prestigious awards such as the Social Choice and Welfare Prize and the John von Neumann Award. Additionally, he has held editorial roles for prominent journals including Games and Economic Behavior, Review of Economic Design, and Econometrica, further underscoring his impact on the field of economics. Through his research and teaching, Jackson continues to advance our understanding of complex economic systems and their underlying social structures.
Innovator at the Intersection of Computer Science and Economics
Kevin Leyton-Brown is a prominent professor of Computer Science at the University of British Columbia, where he also serves as an associate member of the Vancouver School of Economics. Since earning his PhD from Stanford University in 2003, he has focused his research on the intersection of computer science and microeconomics, tackling computational challenges within economic contexts and exploring incentive structures in multiagent systems. His work extends to applying machine learning for the automated design and analysis of algorithms aimed at solving complex computational problems. Leyton-Brown's contributions to the field have been recognized with numerous awards, including UBC's Charles A. McDowell Award for Excellence in Research and a NSERC E.W.R. Steacie Memorial Fellowship. He has also received accolades for his teaching and research from various organizations, including the Canadian Association of Computer Science. As an influential figure in his field, he chairs the ACM Special Interest Group on Electronic Commerce and serves as an associate editor for several prestigious journals. Through his innovative research and educational initiatives, Leyton-Brown continues to shape the future of economics and computer science integration.
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4.7 course rating
614 ratings
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