212 research outputs found
Simplicity-Expressiveness Tradeoffs in Mechanism Design
A fundamental result in mechanism design theory, the so-called revelation
principle, asserts that for many questions concerning the existence of
mechanisms with a given outcome one can restrict attention to truthful direct
revelation-mechanisms. In practice, however, many mechanism use a restricted
message space. This motivates the study of the tradeoffs involved in choosing
simplified mechanisms, which can sometimes bring benefits in precluding bad or
promoting good equilibria, and other times impose costs on welfare and revenue.
We study the simplicity-expressiveness tradeoff in two representative settings,
sponsored search auctions and combinatorial auctions, each being a canonical
example for complete information and incomplete information analysis,
respectively. We observe that the amount of information available to the agents
plays an important role for the tradeoff between simplicity and expressiveness
K-Implementation
This paper discusses an interested party who wishes to influence the behavior
of agents in a game (multi-agent interaction), which is not under his control.
The interested party cannot design a new game, cannot enforce agents' behavior,
cannot enforce payments by the agents, and cannot prohibit strategies available
to the agents. However, he can influence the outcome of the game by committing
to non-negative monetary transfers for the different strategy profiles that may
be selected by the agents. The interested party assumes that agents are
rational in the commonly agreed sense that they do not use dominated
strategies. Hence, a certain subset of outcomes is implemented in a given game
if by adding non-negative payments, rational players will necessarily produce
an outcome in this subset. Obviously, by making sufficiently big payments one
can implement any desirable outcome. The question is what is the cost of
implementation? In this paper we introduce the notion of k-implementation of a
desired set of strategy profiles, where k stands for the amount of payment that
need to be actually made in order to implement desirable outcomes. A major
point in k-implementation is that monetary offers need not necessarily
materialize when following desired behaviors. We define and study
k-implementation in the contexts of games with complete and incomplete
information. In the latter case we mainly focus on the VCG games. Our setting
is later extended to deal with mixed strategies using correlation devices.
Together, the paper introduces and studies the implementation of desirable
outcomes by a reliable party who cannot modify game rules (i.e. provide
protocols), complementing previous work in mechanism design, while making it
more applicable to many realistic CS settings
Bundling Equilibrium in Combinatorial auctions
This paper analyzes individually-rational ex post equilibrium in the VC
(Vickrey-Clarke) combinatorial auctions. If is a family of bundles of
goods, the organizer may restrict the participants by requiring them to submit
their bids only for bundles in . The -VC combinatorial auctions
(multi-good auctions) obtained in this way are known to be
individually-rational truth-telling mechanisms. In contrast, this paper deals
with non-restricted VC auctions, in which the buyers restrict themselves to
bids on bundles in , because it is rational for them to do so. That is,
it may be that when the buyers report their valuation of the bundles in
, they are in an equilibrium. We fully characterize those that
induce individually rational equilibrium in every VC auction, and we refer to
the associated equilibrium as a bundling equilibrium. The number of bundles in
represents the communication complexity of the equilibrium. A special
case of bundling equilibrium is partition-based equilibrium, in which
is a field, that is, it is generated by a partition. We analyze the tradeoff
between communication complexity and economic efficiency of bundling
equilibrium, focusing in particular on partition-based equilibrium
Allocative and Informational Externalities in Auctions and Related Mechanisms
We study the effects of allocative and informational externalities in (multi-object) auctions and related mechanisms. Such externalities naturally arise in models that embed auctions in larger economic contexts. In particular, they appear when there is downstream interaction among bidders after the auction has closed. The endogeneity of valuations is the main driving force behind many new, specific phenomena with allocative externalities: even in complete information settings, traditional auction formats need not be efficient, and they may give rise to multiple equilibria and strategic non-participation. But, in the absence of informational externalities, welfare maximization can be achieved by Vickrey-Clarke- Groves mechanisms. Welfare-maximizing Bayes-Nash implementation is, however, impossible in multi-object settings with informational externalities, unless the allocation problem is separable across objects (e.g. there are no allocative externalities nor complementarities) or signals are one-dimensional. Moreover, implementation of any choice function via ex-post equilibrium is generically impossible with informational externalities and multidimensional types. A theory of information constraints with multidimensional signals is rather complex, but indispensable for our study
Price-Based Combinatorial Auction: Connectedness and Representative Valuations
We investigate combinatorial auctions from a practical perspective. The auctioneer gathers information according to a dynamical protocol termed ask price procedure. We demonstrate a method for elucidating whether a procedure gathers sufficient information for deriving a VCG mechanism. We calculate representative valuation functions in a history-contingent manner, and show that it is necessary and sufficient to examine whether efficient allocations with and without any buyer associated with the profile of representative valuation functions were revealed. This method is tractable, and can be applied to general procedures with connectedness. The representative valuation functions could be the sufficient statistics for privacy preservation.
Computational Efficiency Requires Simple Taxation
We characterize the communication complexity of truthful mechanisms. Our
departure point is the well known taxation principle. The taxation principle
asserts that every truthful mechanism can be interpreted as follows: every
player is presented with a menu that consists of a price for each bundle (the
prices depend only on the valuations of the other players). Each player is
allocated a bundle that maximizes his profit according to this menu. We define
the taxation complexity of a truthful mechanism to be the logarithm of the
maximum number of menus that may be presented to a player.
Our main finding is that in general the taxation complexity essentially
equals the communication complexity. The proof consists of two main steps.
First, we prove that for rich enough domains the taxation complexity is at most
the communication complexity. We then show that the taxation complexity is much
smaller than the communication complexity only in "pathological" cases and
provide a formal description of these extreme cases.
Next, we study mechanisms that access the valuations via value queries only.
In this setting we establish that the menu complexity -- a notion that was
already studied in several different contexts -- characterizes the number of
value queries that the mechanism makes in exactly the same way that the
taxation complexity characterizes the communication complexity.
Our approach yields several applications, including strengthening the
solution concept with low communication overhead, fast computation of prices,
and hardness of approximation by computationally efficient truthful mechanisms
Reallocation Mechanisms
We consider reallocation problems in settings where the initial endowment of
each agent consists of a subset of the resources. The private information of
the players is their value for every possible subset of the resources. The goal
is to redistribute resources among agents to maximize efficiency. Monetary
transfers are allowed, but participation is voluntary.
We develop incentive-compatible, individually-rational and budget balanced
mechanisms for several classic settings, including bilateral trade, partnership
dissolving, Arrow-Debreu markets, and combinatorial exchanges. All our
mechanisms (except one) provide a constant approximation to the optimal
efficiency in these settings, even in ones where the preferences of the agents
are complex multi-parameter functions
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