As infrastructure-as-a-service clouds become more popular, cloud providers face the complicated problem of maximizing their resource utilization by handling the dynamics of user demand. Auction-based pricing, such as Amazon EC2 spot pricing, provides an option for users to use idle resources at highly reduced yet dynamic prices; under such a pricing scheme, users place bids for cloud resources,...

ITERATIVE COMBINATORIAL AUCTIONS: ACHIEVING ECONOMIC AND COMPUTATIONAL EFFICIENCY David Christopher Parkes Supervisor: Lyle H. Ungar A fundamental problem in building open distributed systems is to design mechanisms that compute optimal system-wide solutions despite the self-interest of individual users and computational agents. Classic game-theoretic solutions are often prohibitively expensive...

According to a recently introduced theory (Spann, Zeithammer and Häubl 2010), a name-your-own-price retailer should benefit from charging prospective buyers a non-refundable bidding fee rather than providing the bidding opportunity free of charge. We use an incentive-compatible experiment to provides the first empirical test of the profitability of bidding fees. Confirming the theory’s qualitat...

Display advertisements are a type of web advertisement, which are usually images or movies that are displayed as a part of web page. In a display advertisement market we consider that media sites (advertising media) are sellers, that ad spaces are goods, and that advertisers are buyers. Previously, a fixed price was set for displaying advertisements and ad agencies mediated the transaction. How...

Information about the opponent is essential to improve automated negotiation strategies for bilateral multi-issue negotiation. In this paper we propose a negotiation strategy that combines a Bayesian technique to learn the preferences of an opponent during bidding and a Tit-for-Tat-like strategy to avoid exploitation by the opponent. The learned opponent model is used to achieve two important g...

Information about the opponent is essential to improve automated negotiation strategies for bilateral multi-issue negotiation. In this paper we propose a negotiation strategy that combines a Bayesian technique to learn the preferences of an opponent during bidding and a Tit-for-Tat-like strategy to avoid exploitation by the opponent. The learned opponent model is used to achieve two important g...

Prospective payment encourages managed care organizations to select low-risk patients. This article models an entitlement program utilizing patient-level competitive bidding to mitigate risk selection. Three mechanisms are tested: uniform payment, pure bidding, and a mix of payment and bidding. Results show selection always occurs under optimal uniform payment, but never under either bidding me...

This work is concerned with the application of game-theoretic principles to model competition between demand response aggregators for selling excess energy stored in electrochemical storage devices directly to other aggregators in a power market. This market framework is presented as an alternative to the traditional vertically-integrated market structure, which may be better suited for develop...

We study a procurement setting in which the buyer seeks a low price but will not allocate the contract to a supplier who has not passed qualification screening. Qualification screening is costly for the buyer, involving product tests, site visits, and interviews. In addition to a qualified incumbent supplier, the buyer has an entrant of unknown qualification. The buyer wishes to run a price-onl...

Whilst it can be highly desirable for software agents to engage in auctions, they are normally restricted to trading within known auctions, due to the complexity and heterogeneity of the auction rules within an e-commerce system. To allow for agents to deal with previously unseen protocols, we present a proof-carrying code approach using Coq wherein auction protocols can be specified and desira...