376,437 research outputs found
Truthful Assignment without Money
We study the design of truthful mechanisms that do not use payments for the
generalized assignment problem (GAP) and its variants. An instance of the GAP
consists of a bipartite graph with jobs on one side and machines on the other.
Machines have capacities and edges have values and sizes; the goal is to
construct a welfare maximizing feasible assignment. In our model of private
valuations, motivated by impossibility results, the value and sizes on all
job-machine pairs are public information; however, whether an edge exists or
not in the bipartite graph is a job's private information.
We study several variants of the GAP starting with matching. For the
unweighted version, we give an optimal strategyproof mechanism; for maximum
weight bipartite matching, however, we show give a 2-approximate strategyproof
mechanism and show by a matching lowerbound that this is optimal. Next we study
knapsack-like problems, which are APX-hard. For these problems, we develop a
general LP-based technique that extends the ideas of Lavi and Swamy to reduce
designing a truthful mechanism without money to designing such a mechanism for
the fractional version of the problem, at a loss of a factor equal to the
integrality gap in the approximation ratio. We use this technique to obtain
strategyproof mechanisms with constant approximation ratios for these problems.
We then design an O(log n)-approximate strategyproof mechanism for the GAP by
reducing, with logarithmic loss in the approximation, to our solution for the
value-invariant GAP. Our technique may be of independent interest for designing
truthful mechanisms without money for other LP-based problems.Comment: Extended abstract appears in the 11th ACM Conference on Electronic
Commerce (EC), 201
A Survey on Approximation Mechanism Design without Money for Facility Games
In a facility game one or more facilities are placed in a metric space to
serve a set of selfish agents whose addresses are their private information. In
a classical facility game, each agent wants to be as close to a facility as
possible, and the cost of an agent can be defined as the distance between her
location and the closest facility. In an obnoxious facility game, each agent
wants to be far away from all facilities, and her utility is the distance from
her location to the facility set. The objective of each agent is to minimize
her cost or maximize her utility. An agent may lie if, by doing so, more
benefit can be obtained. We are interested in social choice mechanisms that do
not utilize payments. The game designer aims at a mechanism that is
strategy-proof, in the sense that any agent cannot benefit by misreporting her
address, or, even better, group strategy-proof, in the sense that any coalition
of agents cannot all benefit by lying. Meanwhile, it is desirable to have the
mechanism to be approximately optimal with respect to a chosen objective
function. Several models for such approximation mechanism design without money
for facility games have been proposed. In this paper we briefly review these
models and related results for both deterministic and randomized mechanisms,
and meanwhile we present a general framework for approximation mechanism design
without money for facility games
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