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Course CSE691
Title Spring 2014 : Advanced Topics in Computer Science: Computational Game Theory
Fall 2014      : Energy Efficient Computing

Spring 2014
Computational game theory is a quickly developing area at the interface of computer science and economics. It was largely motivated by the emergence of the Internet and the trend of making strategic decisions online. Indeed, more and more “entities” in our systems are switching from mindless devices that honestly run whatever algorithms or protocols they have been given, to strategic players. Examples include auctions, social networks, and crowdsourcing systems.

Designing such systems is challenging, because it is unlikely for the designer to have all the data needed to improve the performance of the systems, and he or she must find reliable ways to elicit the correct data from players who rationally and selfishly act so as to maximize their own utilities. It is even more challenging when the computational resources of the designer or the players are limited, when the players may form coalitions and coordinate their strategies, or when the players may have privacy concerns about revealing information about themselves.

This course is about analyzing and designing such systems using ideas from algorithms, cryptography, and game theory. We shall start with fundamental concepts and techniques in game theory, and gradually proceed to the state of the art in computational game theory. On the way we shall see how Computer Science and Economics are affecting each other. Topics include but not limited to: games, equilibria, auctions, single-parameter games, mechanism design, and crowdsourcing.

Fall 2014
Energy is an important resource for today's computer systems ranging from laptops (think battery life) all the way up to entire data centers and clouds (staggering electricity bills). There has been a lot of recent research on the topic of improving energy efficiency (Green Computing). This research cuts across different areas of computer science including Computer Architecture (ex: energy-efficient processor design), Networking (ex: putting the network to sleep), Storage (ex: exploiting idle I/O periods to spin down disks), Distributed Systems (ex: capacity provisioning), and Modeling/Analytics (ex: modeling a server's power consumption). This course will cover the recent research trends in energy-efficient computing, focusing specifically on themes and techniques for achieving energy efficiency in computer systems. This is a seminar course and will involve research paper discussions and a semester-long project. The goal of this course is to educate students to the extent that they can conduct their own energy-efficieny research in their area of interest.

Prerequisite Basic knowledge of probability, algorithms, and (very basic) computational complexity. Interested students without a computational background are encouraged to register, in particular students in economics and mathematics. Such students should discuss with the instructor before the course starts about background issues. Requirements may be adjusted to take background disadvantages (and advantages) into account.
Credit Information 3 credits

The following textbooks are recommended:

  • An Introduction to Game Theory. M. J. Osborne. Oxford University Press.
  • Algorithmic Game Theory. N. Nisan, T. Roughgarden, E. Tardos, and V. Vazirani (Eds). Cambridge University Press.

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