David C. Parkes

Computational-mechanism design: a call to arms

Computational-mechanism design has an important role to play in developing complex distributed systems comprising multiple interacting agents. Game theory has developed powerful tools for analyzing, predicting, and controlling the behavior of self-interested agents and decision making in systems with multiple autonomous actors. These tools, when tailored to computational settings, provide a foundation for building multiagent software systems. This tailoring gives rise to the field of computational-mechanism design, which applies economic principles to computer systems design.

i Bundle: an efficient ascending price bundle auction

Standard auction mechanisms often break down in important e-commerce applications, where agents demand bundles of complementary resources, i.e. “I only want B if I also get A”. This paper describes zBundle, an ascending-price auction that is guaranteed to compute optimal bundle allocations with agents that follow a best-response bidding strategy. The auction prices bundles directly and allows agents to place additive or exclusive-or bids over collections of bundles. Empirical results confirm that iBundle generates efficient allocations for hard resource allocation problems. Furthermore, we show that iBundle generates solutions without complete revelation (or computation) of agent preferences.

Rationality and Self-Interest in Peer to Peer Networks

Much of the existing work in peer to peer networking assumes that users will follow prescribed protocols without deviation. This assumption ignores the user’s ability to modify the behavior of an algorithm for self-interested reasons. We advocate a different model in which peer to peer users are expected to be rational and self-interested. This model is found in the emergent fields of Algorithmic Mechanism Design (AMD) and Distributed Algorithmic Mechanism Design (DAMD), both of which introduce game-theoretic ideas into a computational system. We, as designers, must create systems (peer to peer search, routing, distributed auctions, resource allocation, etc.) that allow nodes to behave rationally while still achieving good overall system outcomes. This paper has three goals. The first is to convince the reader that rationality is a real issue in peer to peer networks. The second is to introduce mechanism design as a tool that can be used when designing networks with rational nodes. The third is to describe three open problems that are relevant in the peer to peer setting but are unsolved in existing AMD/DAMD work. In particular, we consider problems that arise when a networking infrastructure contains rational agents.

Models for Iterative Multiattribute Procurement Auctions

Multiattribute auctions extend traditional auction settings to allow negotiation over nonprice attributes such as weight, color, and terms of delivery, in addition to price and promise to improve market efficiency in markets with configurable goods. This paper provides an iterative auction design for an important special case of the multiattribute allocation problem with special (preferential independent) additive structure on the buyer value and seller costs. Auction Additive&Discrete provides a refined design for a price-based auction in which the price feedback decomposes to an additive part with a price for each attribute and an aggregate part that appears as a price discount for each supplier. In addition, this design also has excellent information revelation properties that are validated through computational experiments. The auction terminates with an outcome of a modified Vickrey-Clarke-Groves mechanism. This paper also develops Auction NonLinear&Discrete for the more general nonlinear case-a particularly simple design that solves the general multiattribute allocation problem, but requires that the auctioneer maintains prices on bundles of attribute levels.

Adaptive limited-supply online auctions

We study a limited-supply online auction problem, in which an auctioneer has k goods to sell and bidders arrive and depart dynamically. We suppose that agent valuations are drawn independently from some unknown distribution and construct an adaptive auction that is nevertheless value- andtime-strategy proof. For the k=1 problem we have a strategyproof variant on the classic secretary problem. We present a 4-competitive (e-competitive) strategyproof online algorithm with respect to offline Vickrey for revenue (efficiency). We also show (in a model that slightly generalizes the assumption of independent valuations) that no mechanism can be better than 3/2-competitive (2-competitive) for revenue (efficiency). Our general approach considers a learning phase followed by an accepting phase, and is careful to handle incentive issues for agents that span the two phases. We extend to the k›1 case, by deriving strategyproof mechanisms which are constant-competitive for revenue and efficiency. Finally, we present some strategyproof competitive algorithms for the case in which adversary uses a distribution known to the mechanism.

The price of selfish behavior in bilateral network formation

Given a collection of selfish agents who wish to establish links to route traffic among themselves, the set of equilibrium network topologies may appear quite different from the centrally enforced optimum. We study the quality (price of anarchy) of equilibrium networks in a game where links require the consent of both participants and are negotiated bilaterally and compare these networks to those generated by an earlier model due to Fabrikant et al. [6] in which links are formed unilaterally. We provide a characterization of stable and efficient networks in the bilateral network formation game, show that the set of stable networks is richer than those in the unilateral game, and that all stable networks of the unilateral game are also stable in the bilateral game. We also provide an upper and lower bound on the price of anarchy (tight in the size of the network n but not the link cost α) of the bilateral game and show that the worst-case price of anarchy of the bilateral model is worse than for the unilateral model. A careful empirical analysis demonstrates that the average price of anarchy is better in the bilateral connection game than in the unilateral game for small link costs but worse as links become more expensive. In the process, a powerful equivalence between link-based graph stability and two game-theoretic equilibrium notions is also discussed. The equivalence establishes necessary and sufficient conditions for an equilibrium in the bilateral game that helps provide a partial geometric characterization of equilibrium graphs.

Human computation tasks with global constraints

An important class of tasks that are underexplored in current human computation systems are complex tasks with global constraints. One example of such a task is itinerary planning, where solutions consist of a sequence of activities that meet requirements specified by the requester. In this paper, we focus on the crowdsourcing of such plans as a case study of constraint-based human computation tasks and introduce a collaborative planning system called Mobi that illustrates a novel crowdware paradigm. Mobi presents a single interface that enables crowd participants to view the current solution context and make appropriate contributions based on current needs. We conduct experiments that explain how Mobi enables a crowd to effectively and collaboratively resolve global constraints, and discuss how the design principles behind Mobi can more generally facilitate a crowd to tackle problems involving global constraints.

Beyond dominant resource fairness: extensions, limitations, and indivisibilities

We study the problem of allocating multiple resources to agents with heterogeneous demands. Technological advances such as cloud computing and data centers provide a new impetus for investigating this problem under the assumption that agents demand the resources in fixed proportions, known in economics as Leontief preferences. In a recent paper, Ghodsi et al. [2011] introduced the dominant resource fairness (DRF) mechanism, which was shown to possess highly desirable theoretical properties under Leontief preferences. We extend their results in three directions. First, we show that DRF generalizes to more expressive settings, and leverage a new technical framework to formally extend its guarantees. Second, we study the relation between social welfare and properties such as truthfulness; DRF performs poorly in terms of social welfare, but we show that this is an unavoidable shortcoming that is shared by every mechanism that satisfies one of three basic properties. Third, and most importantly, we study a realistic setting that involves indivisibilities. We chart the boundaries of the possible in this setting, contributing a new relaxed notion of fairness and providing both possibility and impossibility results.

Pricing WiFi at Starbucks: issues in online mechanism design

We consider the problem of designing mechanisms for online problems in which agents arrive over time and truthfully announce their arrival. These problems are becoming extremely common in a wide variety of problems involving wireless networking and webserving. We show how the standard results of mechanism design can be modified to apply to this setting, provide conditions under which efficient and incentive compatible mechanisms exist and analyze several important online models including wireless networks and web serving.

Auctions, Bidding and Exchange Design

Auctions have found widespread use in the last few years as a technique for supporting and automating negotiations on the Internet. For example, eBay now serves as a new selling channel for individuals, and small and big enterprises. Another use for auctions is for industrial procurement. In both these settings traditional auction mechanisms such as the English, Dutch, First (or Second) price Sealed-Bid auctions are now commonplace. These auctions types are useful for settings where there is a single unit of an item being bought/sold. However, since procurement problems are business-to-business they tend to be more complex and have led to the development and application of advanced auction types that allow for negotiations over multiple units of multiple items, and the configuration of the attributes of items. At the heart of auctions is the problem of decentralized resource allocation.