789 research outputs found
Auctions with Heterogeneous Items and Budget Limits
We study individual rational, Pareto optimal, and incentive compatible
mechanisms for auctions with heterogeneous items and budget limits. For
multi-dimensional valuations we show that there can be no deterministic
mechanism with these properties for divisible items. We use this to show that
there can also be no randomized mechanism that achieves this for either
divisible or indivisible items. For single-dimensional valuations we show that
there can be no deterministic mechanism with these properties for indivisible
items, but that there is a randomized mechanism that achieves this for either
divisible or indivisible items. The impossibility results hold for public
budgets, while the mechanism allows private budgets, which is in both cases the
harder variant to show. While all positive results are polynomial-time
algorithms, all negative results hold independent of complexity considerations
Principal-agent VCG contracts
We study a complete information game with multiple principals and multiple common agents. Each agent takes an action that can affect the payoffs of all principals. Prat and Rustichini (2003) who introduce this model assume classic contracts: each principal offers monetary transfers to each agent conditional on the action taken by the agent. We define VCG contracts in which the monetary transfers to each agent additionally depend on all principals' offers, and study its effect on the existence of efficient pure subgame perfect equilibrium outcomes. Using a necessary and sufficient condition for the existence of a pure subgame perfect equilibrium (pure SPE) with VCG contracts, which we develop, we show that the class of instances that admit an efficient pure SPE with VCG contracts strictly contains the class of instances that admit an efficient pure SPE with classic contracts. In addition, the difference between the former class and the class of instances that admit a ‘weakly truthful’ SPE with classic contracts has positive measure. Although VCG contracts broaden the existence of pure subgame perfect equilibria, we show that the worst case welfare loss in a pure SPE outcome, over all games with any fixed M≥2 number of principals, is the same for both VCG contracts and classic contracts.</p
Budget Feasible Mechanisms for Experimental Design
In the classical experimental design setting, an experimenter E has access to
a population of potential experiment subjects , each
associated with a vector of features . Conducting an experiment
with subject reveals an unknown value to E. E typically assumes
some hypothetical relationship between 's and 's, e.g., , and estimates from experiments, e.g., through linear
regression. As a proxy for various practical constraints, E may select only a
subset of subjects on which to conduct the experiment.
We initiate the study of budgeted mechanisms for experimental design. In this
setting, E has a budget . Each subject declares an associated cost to be part of the experiment, and must be paid at least her cost. In
particular, the Experimental Design Problem (EDP) is to find a set of
subjects for the experiment that maximizes V(S) = \log\det(I_d+\sum_{i\in
S}x_i\T{x_i}) under the constraint ; our objective
function corresponds to the information gain in parameter that is
learned through linear regression methods, and is related to the so-called
-optimality criterion. Further, the subjects are strategic and may lie about
their costs.
We present a deterministic, polynomial time, budget feasible mechanism
scheme, that is approximately truthful and yields a constant factor
approximation to EDP. In particular, for any small and , we can construct a (12.98, )-approximate mechanism that is
-truthful and runs in polynomial time in both and
. We also establish that no truthful,
budget-feasible algorithms is possible within a factor 2 approximation, and
show how to generalize our approach to a wide class of learning problems,
beyond linear regression
Towards More Practical Linear Programming-based Techniques for Algorithmic Mechanism Design
R. Lavy and C. Swamy (FOCS 2005, J. ACM 2011) introduced a general method for
obtaining truthful-in-expectation mechanisms from linear programming based
approximation algorithms. Due to the use of the Ellipsoid method, a direct
implementation of the method is unlikely to be efficient in practice. We
propose to use the much simpler and usually faster multiplicative weights
update method instead. The simplification comes at the cost of slightly weaker
approximation and truthfulness guarantees
COMPUTATIONAL AERODYNAMIC STUDY OF A HATCHBACK CAR MODEL
"Ahmed Body" is a well-established model of a hatchback car. In this study, computational simulations were conducted by using existing CFD software to capture "drag crisis" phenomena. Flow is assumed as incompressible flow with Reynolds Number of 4.3 x 10^6. A half of "Ahmed Body" was used in computational simulations with RANS method. Turbulence models that were employed mostly are k-e. The amount of grid cells used in computation is about 300.000. Computations were carried out mostly to get drag coefficients and also to examine vortex structure related to it. In "drag crisis" phenomena, maximum drag coefficient is reached at rear window angle of 30 degrees. Placement of spoilers and vortex generator has succesfully reduced the maximum drag coefficient at the critical angle of 30 degrees
Efficiency Guarantees in Auctions with Budgets
In settings where players have a limited access to liquidity, represented in
the form of budget constraints, efficiency maximization has proven to be a
challenging goal. In particular, the social welfare cannot be approximated by a
better factor then the number of players. Therefore, the literature has mainly
resorted to Pareto-efficiency as a way to achieve efficiency in such settings.
While successful in some important scenarios, in many settings it is known that
either exactly one incentive-compatible auction that always outputs a
Pareto-efficient solution, or that no truthful mechanism can always guarantee a
Pareto-efficient outcome. Traditionally, impossibility results can be avoided
by considering approximations. However, Pareto-efficiency is a binary property
(is either satisfied or not), which does not allow for approximations.
In this paper we propose a new notion of efficiency, called \emph{liquid
welfare}. This is the maximum amount of revenue an omniscient seller would be
able to extract from a certain instance. We explain the intuition behind this
objective function and show that it can be 2-approximated by two different
auctions. Moreover, we show that no truthful algorithm can guarantee an
approximation factor better than 4/3 with respect to the liquid welfare, and
provide a truthful auction that attains this bound in a special case.
Importantly, the liquid welfare benchmark also overcomes impossibilities for
some settings. While it is impossible to design Pareto-efficient auctions for
multi-unit auctions where players have decreasing marginal values, we give a
deterministic -approximation for the liquid welfare in this setting
Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes
An online problem called dynamic resource allocation with capacity constraints (DRACC) is introduced and studied in the realm of posted price mechanisms. This problem subsumes several applications of stateful pricing, including but not limited to posted prices for online job scheduling and matching over a dynamic bipartite graph. Because existing online learning techniques do not yield vanishing regret for this problem, we develop a novel online learning framework over deterministic Markov decision processes with dynamic state transition and reward functions. Following that, we prove, based on a reduction to the well-studied problem of online learning with switching costs, that if the Markov decision process admits a chasing oracle (i.e., an oracle that simulates any given policy from any initial state with bounded loss), then the online learning problem can be solved with vanishing regret. Our results for the DRACC problem and its applications are then obtained by devising (randomized and deterministic) chasing oracles that exploit the particular structure of these problems
Full-scale ground proximity investigation of a VTOL fighter model aircraft
Exhaust gas ingestion characteristics and induced aerodynamics for vertical takeoff lift engine fighter model in ground proximit
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