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Game-Theoretic Sponsored Search and Human Computation
PhD Thesis Proposal Defence
Title: "Game-Theoretic Sponsored Search and Human Computation"
by
Mr. Georgios TRIMPONIAS
Abstract:
This thesis applies concepts and tools from game theory in two areas with
immense industrial potential, sponsored search and human computation. In
sponsored search, we investigate contextualized advertising, where
advertisers have different valuations for different disjoint contexts and
the number of queries per context is known in advance. When no budget
constraints exist, we properly adapt the GSP auction, and explore
combinatorial auctions. When budget constraints are present, we
distinguish between two cases: advertisers may be indifferent to the price
per click, or they may not be willing to pay more than their valuation.
For the first case, we utilize a novel probabilistic framework that is
inspired by resource allocation markets. Under reasonable conditions, a
Nash equilibrium always exists; to compute it, we introduce three methods
based on distributed dynamics. In the second case, we cannot show that a
Nash equilibrium always exists, but we manage to bound a player??s most
profitable deviation using concave relaxations of the utilities. In human
computation, we address two fundamental problems in human computation
games. The first concerns methods for ranking players according to their
skill. We discuss how human computation games are weak-link games, where
low-skill players have a disproportionately greater impact on the game
outcome. We then develop three ELO-based techniques that consider the
weak-link structure as well as the task difficulty. Moreover, we introduce
a Bayesian skill rating system, and show how to perform approximate
inference using Expectation Propagation and a proportional heuristic for
updating the posterior marginals. The second problem regards the mechanism
design for generalizations of the ESP game. We apply Bayesian game theory
to model and analyze how players behave in equilibrium. Our analysis
explains how rational and strategic players may resort to adversarial
actions to increase their score. To tackle this, we introduce an improved
proportional mechanism.
Date: Friday, 14 November 2014
Time: 2:00pm - 4:00pm
Venue: Room 3494
lifts 25/26
Committee Members: Prof. Qiang Yang (Supervisor)
Prof. Dimitris Papadias (Chairperson)
Prof. Dit-Yan Yeung
Prof. Yang Wang (MATH)
**** ALL are Welcome ****