This exciting and pioneering new overview of multiagent systems, which are online systems composed of multiple interacting intelligent agents, i.e., online trading, offers a newly seen computer science perspective on multiagent systems, while integrating ideas from operations research, game theory, economics, logic, and even philosophy and linguistics. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming. Written by two of the leading researchers of this engaging field, this book will surely serve as THE reference for researchers in the fastest-growing area of computer science, and be used as a text for advanced undergraduate or graduate courses.

Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations

A new era of theoretical computer science addresses fundamental problems about auctions, networks, and human behavior.

http://www.maths.lse.ac.uk/Personal/stengel/TEXTE/agt-stengel.pdf

Algorithmic Game Theory

We investigate the "generalized second-price" (GSP) auction, a new mechanism used by search engines to sell online advertising. Although GSP looks similar to the Vickrey-Clarke-Groves (VCG) mechanism, its properties are very different. Unlike the VCG mechanism, GSP generally does not have an equilibrium in dominant strategies, and truth-telling is not an equilibrium of GSP. To analyze the properties of GSP, we describe the generalized English auction that corresponds to GSP and show that it has a unique equilibrium. This is an ex post equilibrium, with the same payoffs to all players as the dominant strategy equilibrium of VCG.

/pdf/internet-advertising-and-the-generalized-second-price-1uh5jxi66t.pdf

Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords

Search engine advertising has become a significant element of the Web browsing experience. Choosing the right ads for the query and the order in which they are displayed greatly affects the probability that a user will see and click on each ad. This ranking has a strong impact on the revenue the search engine receives from the ads. Further, showing the user an ad that they prefer to click on improves user satisfaction. For these reasons, it is important to be able to accurately estimate the click-through rate of ads in the system. For ads that have been displayed repeatedly, this is empirically measurable, but for new ads, other means must be used. We show that we can use features of ads, terms, and advertisers to learn a model that accurately predicts the click-though rate for new ads. We also show that using our model improves the convergence and performance of an advertising system. As a result, our model increases both revenue and user satisfaction.

/pdf/predicting-clicks-estimating-the-click-through-rate-for-new-5b9f38ivaq.pdf

Predicting clicks: estimating the click-through rate for new ads

S4 is a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that allows programmers to easily develop applications for processing continuous unbounded streams of data. Keyed data events are routed with affinity to Processing Elements (PEs), which consume the events and do one or both of the following: (1) emit one or more events which may be consumed by other PEs, (2) publish results. The architecture resembles the Actors model, providing semantics of encapsulation and location transparency, thus allowing applications to be massively concurrent while exposing a simple programming interface to application developers. In this paper, we outline the S4 architecture in detail, describe various applications, including real-life deployments. Our design is primarily driven by large scale applications for data mining and machine learning in a production environment. We show that the S4 design is surprisingly flexible and lends itself to run in large clusters built with commodity hardware.

/pdf/s4-distributed-stream-computing-platform-3mh9t7maap.pdf

S4: Distributed Stream Computing Platform

We estimate parameters from data on discrete dynamic games, using entry/exit games to illustrate. Semiparametric first-stage estimates of entry and continuation values are computed from sample averages of the realized continuation values of entrants and incumbents. Under certain assumptions, these values are easy-to-compute analytic functions of the parameters of interest. The entry and continuation values are used to determine the model’s predictions for entry and exit conditional on the parameter vector, and the estimates compare these predictions with the data on entry and exit rates. Small-sample properties are discussed and lead to the simplest of estimators.

/pdf/simple-estimators-for-the-parameters-of-discrete-dynamic-d1quiu6gej.pdf

Simple estimators for the parameters of discrete dynamic games (with entry/exit examples)

We examine sponsored search auctions run by Overture (now part of Yahoo!) and Google and present evidence of strategic bidder behavior in these auctions. Between June 15, 2002, and June 14, 2003, we estimate that Overture's revenue might have been higher if it had been able to prevent this strategic behavior. We present an alternative mechanism that could reduce the amount of strategizing by bidders, raise search engines' revenues, and increase the efficiency of the market. We conclude by showing that strategic behavior has not disappeared over time; it remains present on both search engines.

/pdf/strategic-bidder-behavior-in-sponsored-search-auctions-3uysjy2tnk.pdf

Strategic bidder behavior in sponsored search auctions

This paper presents a theory of matching in vertical networks, generalizing the theory of matching in two-sided markets introduced by Gale and Shapley. Under natural restrictions, stable networks are guaranteed to exist. The set of stable networks is a lattice, with side-optimal stable networks at the extremes. Several other key results on two-sided matching also extend naturally to the more general setting.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID700848_code107225.pdf?abstractid=700848&mirid=3

Stability in Supply Chain Networks

We present the results of a large field experiment on setting reserve prices in auctions for online advertisements, guided by the theory of optimal auction design suitably adapted to the sponsored search setting. Consistent with the theory, following the introduction of new reserve prices revenues in these auctions have increased substantially.

Michael Ostrovsky

Papers

Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords

Simple estimators for the parameters of discrete dynamic games (with entry/exit examples)

Strategic bidder behavior in sponsored search auctions

Stability in Supply Chain Networks

Reserve Prices in Internet Advertising Auctions: A Field Experiment