Module Description
This module prepares students to understand and design the kinds of systems that are coming to define modern life, such as Amazon, Uber, eBay, etc. These companies need analysts who can decide which objectives to maximize, what information and choices to offer, what rules to set, and so on. These questions require a broad understanding of topics at the interface of theoretical computer science and economics. This module will take a computational and algorithmic approach to designing and analyzing such systems. Students will explore the interaction between self-interested agents and strategic scenarios through the lens of Algorithmic Game Theory and Mechanism Design.Aims
Algorithmic game theory lies at the exciting intersection of CS and Economics and is an area of expertise that is in great demand within the UK Finance Industry, forming one of the primary recruiting sectors for graduates from Computer Science. The aim of this module is to introduce this subject to students using research-led teaching that uses expertise from staff within the Centre for Computational Finance and Economic Agents (CCFEA) at the University of Essex. This model also provides an excellent opportunity for students to explore continuing their studies in a postgraduate CCFEA degree programme.Learning Outcomes
By the end of this module, students will:1. Be able to model various situations as strategic games
2. Understand and use computational and algorithmic aspects of game theory
3. Appreciate incentive structures used in certain situations
4. Carry out a model of a realistic scenario, perform evaluations and draw conclusions from the model evaluation.
Outline Syllabus
Game Theory Basics:
- Mixed Strategies, Expected Payoffs, and Nash Equilibrium.
- 2-Player Zero-Sum Games, and The Minimax Theorem, Introduction to Linear
Programming
Auctions and Mechanism Design Basics;
Algorithms and complexity theory basics
Current research challenges in algorithmic game theory.
- Selfish Network Routing, Congestion Games, and the Price of Anarchy
Auctions and Mechanism Design Basics;
- Auctions as games, Bayesian games, and Vickrey auctions
- Matching Markets, unit-demand auctions, and VCG
- Revenue maximizing auctions, and Simple auctions
- Combinatorial auctions
- Online auctions, sponsored search auctions
- Mechanism design without money
Algorithms and complexity theory basics
- learning and computing Nash and market equilibria
- NP-Completeness, PLS-Completeness, PPAD-Completeness
Current research challenges in algorithmic game theory.
Category: Undergraduate