994 research outputs found
Condorcet-Consistent and Approximately Strategyproof Tournament Rules
We consider the manipulability of tournament rules for round-robin
tournaments of competitors. Specifically, competitors are competing for
a prize, and a tournament rule maps the result of all
pairwise matches (called a tournament, ) to a distribution over winners.
Rule is Condorcet-consistent if whenever wins all of her matches,
selects with probability .
We consider strategic manipulation of tournaments where player might
throw their match to player in order to increase the likelihood that one of
them wins the tournament. Regardless of the reason why chooses to do this,
the potential for manipulation exists as long as increases by
more than decreases. Unfortunately, it is known that every
Condorcet-consistent rule is manipulable (Altman and Kleinberg). In this work,
we address the question of how manipulable Condorcet-consistent rules must
necessarily be - by trying to minimize the difference between the increase in
and decrease in for any potential manipulating
pair.
We show that every Condorcet-consistent rule is in fact -manipulable,
and that selecting a winner according to a random single elimination bracket is
not -manipulable for any . We also show that many
previously studied tournament formats are all -manipulable, and the
popular class of Copeland rules (any rule that selects a player with the most
wins) are all in fact -manipulable, the worst possible. Finally, we consider
extensions to match-fixing among sets of more than two players.Comment: 20 page
Approximately Strategyproof Tournament Rules: On Large Manipulating Sets and Cover-Consistence
We consider the manipulability of tournament rules, in which n teams play a round robin tournament and a winner is (possibly randomly) selected based on the outcome of all binom{n}{2} matches. Prior work defines a tournament rule to be k-SNM-? if no set of ? k teams can fix the ? binom{k}{2} matches among them to increase their probability of winning by >? and asks: for each k, what is the minimum ?(k) such that a Condorcet-consistent (i.e. always selects a Condorcet winner when one exists) k-SNM-?(k) tournament rule exists?
A simple example witnesses that ?(k) ? (k-1)/(2k-1) for all k, and [Jon Schneider et al., 2017] conjectures that this is tight (and prove it is tight for k=2). Our first result refutes this conjecture: there exists a sufficiently large k such that no Condorcet-consistent tournament rule is k-SNM-1/2. Our second result leverages similar machinery to design a new tournament rule which is k-SNM-2/3 for all k (and this is the first tournament rule which is k-SNM-(<1) for all k).
Our final result extends prior work, which proves that single-elimination bracket with random seeding is 2-SNM-1/3 [Jon Schneider et al., 2017], in a different direction by seeking a stronger notion of fairness than Condorcet-consistence. We design a new tournament rule, which we call Randomized-King-of-the-Hill, which is 2-SNM-1/3 and cover-consistent (the winner is an uncovered team with probability 1)
Approximation Schemes for a Unit-Demand Buyer with Independent Items via Symmetries
We consider a revenue-maximizing seller with items facing a single buyer.
We introduce the notion of symmetric menu complexity of a mechanism, which
counts the number of distinct options the buyer may purchase, up to
permutations of the items. Our main result is that a mechanism of
quasi-polynomial symmetric menu complexity suffices to guarantee a
-approximation when the buyer is unit-demand over independent
items, even when the value distribution is unbounded, and that this mechanism
can be found in quasi-polynomial time.
Our key technical result is a polynomial time, (symmetric)
menu-complexity-preserving black-box reduction from achieving a
-approximation for unbounded valuations that are subadditive
over independent items to achieving a -approximation when
the values are bounded (and still subadditive over independent items). We
further apply this reduction to deduce approximation schemes for a suite of
valuation classes beyond our main result.
Finally, we show that selling separately (which has exponential menu
complexity) can be approximated up to a factor with a menu of
efficient-linear symmetric menu complexity.Comment: FOCS 201
Trayectoria asistencial en el Trastorno Bipolar
Tesis Doctoral inĂ©dita leĂda en la Universidad AutĂłnoma de Madrid, Facultad de Medicina, Departamento de PsiquiatrĂa. Fecha de Lectura: 03-06-202
Ăkologi-organisationerne og dansk Ăžkologipolitik
Ăkologiorganisationerne spiller en central rolle i dansk Ăžkologipolitik og uden deres aktive medvirken kunne den vanskeligt gennemfĂžres
Physically-based Muscles and Fibers Modeling from Superficial Patches.
We propose a novel approach for the generation of volumetric muscle primitives and their associated fiber field, suitable for simulation in computer animation. Muscles are notoriously difficult to sculpt because of their complex shapes and fiber architecture, therefore often requiring trained artists to render anatomical details. Moreover, physics simulation requires these geometries to be modeled in an intersection-free rest state and to have a spatially-varying fiber field to support contraction with
anisotropic material models. Inspired by the principles of computational design, we satisfy these requirements by generating muscle primitives automatically, complete with tendons and fiber fields, using physics based simulation of inflatable 3D patches which are user-defined on the external mesh of a character
Coding in Undirected Graphs Is Either Very Helpful or Not Helpful at All
While it is known that using network coding can significantly improve the throughput of directed networks, it is a notorious open problem whether coding yields any advantage over the multicommodity flow (MCF) rate in undirected networks. It was conjectured that the answer is no. In this paper we show that even a small advantage over MCF can be amplified to yield a near-maximum possible gap.
We prove that any undirected network with k source-sink pairs that exhibits a (1+epsilon) gap between its MCF rate and its network coding rate can be used to construct a family of graphs G\u27 whose gap is log(|G\u27|)^c for some constant c < 1. The resulting gap is close to the best currently known upper bound, log(|G\u27|), which follows from the connection between MCF and sparsest cuts.
Our construction relies on a gap-amplifying graph tensor product that, given two graphs G1,G2 with small gaps, creates another graph G with a gap that is equal to the product of the previous two, at the cost of increasing the size of the graph. We iterate this process to obtain a gap of log(|G\u27|)^c from any initial gap
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