Learning objectives

Many problems in computer science involve settings where multiple self-interested parties interact, e.g., resource allocation in large networks, online advertising, managing electronic marketplaces and networked computer systems. Computational (algorithmic) game theory complements economic models and solution concepts, to reason about how agents should act when the actions of other agents affect their utilities, with a focus to discuss computational complexity issues, and the use of approximation bounds for models where exact solutions are unrealistic. The course aims to give students an introduction to the main concepts in the field of computational game theory with representative models and (algorithmic) solution chosen to illustrate broader themes. Students will acquire the basic skills to design models and computer systems that performs optimally/well in some paradigmatic multiagent settings; and to reason about the design of mechanisms to incentivate self-interested users to behave in a desirable way.