5,503 research outputs found
Do television and electronic games predict children's psychosocial adjustment? Longitudinal research using the UK Millennium Cohort Study
Background: Screen entertainment for young children has been associated with several aspects of psychosocial adjustment. Most research is from North America and focuses on television. Few longitudinal studies have compared the effects of TV and electronic games, or have investigated gender differences.
Purpose: To explore how time watching TV and playing electronic games at age 5 years each predicts change in psychosocial adjustment in a representative sample of 7 year-olds from the UK.
Methods: Typical daily hours viewing television and playing electronic games at age 5 years were reported by mothers of 11 014 children from the UK Millennium Cohort Study. Conduct problems, emotional symptoms, peer relationship problems, hyperactivity/inattention and prosocial behaviour were reported by mothers using the Strengths and Difficulties Questionnaire. Change in adjustment from age 5 years to 7 years was regressed on screen exposures; adjusting for family characteristics and functioning, and child characteristics.
Results: Watching TV for 3 h or more at 5 years predicted a 0.13 point increase (95% CI 0.03 to 0.24) in conduct problems by 7 years, compared with watching for under an hour, but playing electronic games was not associated with conduct problems. No associations were found between either type of screen time and emotional symptoms, hyperactivity/inattention, peer relationship problems or prosocial behaviour. There was no evidence of gender differences in the effect of screen time.
Conclusions: TV but not electronic games predicted a small increase in conduct problems. Screen time did not predict other aspects of psychosocial adjustment. Further work is required to establish causal mechanisms
Generalizing Boolean Satisfiability I: Background and Survey of Existing Work
This is the first of three planned papers describing ZAP, a satisfiability
engine that substantially generalizes existing tools while retaining the
performance characteristics of modern high-performance solvers. The fundamental
idea underlying ZAP is that many problems passed to such engines contain rich
internal structure that is obscured by the Boolean representation used; our
goal is to define a representation in which this structure is apparent and can
easily be exploited to improve computational performance. This paper is a
survey of the work underlying ZAP, and discusses previous attempts to improve
the performance of the Davis-Putnam-Logemann-Loveland algorithm by exploiting
the structure of the problem being solved. We examine existing ideas including
extensions of the Boolean language to allow cardinality constraints,
pseudo-Boolean representations, symmetry, and a limited form of quantification.
While this paper is intended as a survey, our research results are contained in
the two subsequent articles, with the theoretical structure of ZAP described in
the second paper in this series, and ZAP's implementation described in the
third
Generalizing Boolean Satisfiability III: Implementation
This is the third of three papers describing ZAP, a satisfiability engine
that substantially generalizes existing tools while retaining the performance
characteristics of modern high-performance solvers. The fundamental idea
underlying ZAP is that many problems passed to such engines contain rich
internal structure that is obscured by the Boolean representation used; our
goal has been to define a representation in which this structure is apparent
and can be exploited to improve computational performance. The first paper
surveyed existing work that (knowingly or not) exploited problem structure to
improve the performance of satisfiability engines, and the second paper showed
that this structure could be understood in terms of groups of permutations
acting on individual clauses in any particular Boolean theory. We conclude the
series by discussing the techniques needed to implement our ideas, and by
reporting on their performance on a variety of problem instances
Online mechanism design for electric vehicle charging
The rapid increase in the popularity of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) is expected to place a considerable strain on the existing electricity grids, due to the high charging rates these vehicles require. In many places, the limited capacity of the local electricity distribution network will be exceeded if many such vehicles are plugged in and left to charge their batteries simultaneously. Thus, it will become increasingly important to schedule the charging of these vehicles, taking into account the vehicle ownersâ preferences, and the local constraints on the network. In this paper, we address this setting using online mechanism design and develop a mechanism that incentivises agents (representing vehicle owners) to truthfully reveal their preferences, as well as when the vehicle is available for charging. Existing related online mechanisms assume that agent preferences can be described by a single parameter. However, this is not appropriate for our setting since agents are interested in acquiring multiple units of electricity and can have different preferences for these units, depending on factors such as their expected travel distance. To this end, we extend the state of the art in online mechanism design to multi-valued domains, where agents have non-increasing marginal valuations for each subsequent unit of electricity. Interestingly, we show that, in these domains, the mechanism occasionally requires leaving electricity unallocated to ensure truthfulness. We formally prove that the proposed mechanism is dominant-strategy incentive compatible, and furthermore, we empirically evaluate our mechanism using data from a real-world trial of electric vehicles in the UK. We show that our approach outperforms any fixed price mechanism in terms of allocation efficiency, while performing only slightly worse than a standard scheduling heuristic, which assumes non-strategic agents
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An Ascending-Price Generalized Vickrey Auction
A simple characterization of the equilibrium conditions required to
compute Vickrey payments in the Combinatorial Allocation Problem leads
to an ascending price Generalized Vickrey Auction. The ascending auc-
tion, iBundle Extend & Adjust (iBEA), maintains non-linear and perhaps
non-anonymous prices on bundles of items, and terminates with the ef-
cient allocation and the Vickrey payments in ex post Nash equilibrium.
Crucially, iBEA is able to implement the Vickrey outcome even when the
Vickrey payments are not supported in a single competitive equilibrium.
The auction closes with Universal competitive equilibrium prices, which
provide enough information to compute individualized discounts to adjust
the nal prices and implement Vickrey payments.Engineering and Applied Science
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Iterative Combinatorial Auctions: Theory and Practice
Combinatorial auctions, which allow agents to bid directly for bundles of resources, are necessary for optimal auction-based solutions to resource allocation problems with agents that have non-additive values for resources, such as distributed scheduling and task assignment problems. We introduce iBundle, the first iterative combinatorial auction that is optimal for a reasonable agent bidding strategy, in this case myopic best-response bidding. Its optimality is proved with a novel connection to primal-dual optimization theory. We demonstrate orders of magnitude performance improvements over the only other known optimal combinatorial auction, the Generalized Vickrey Auction.Engineering and Applied Science
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Accounting for Cognitive Costs in On-Line Auction Design
Many auction mechanisms, including first and second price ascending and sealed bid auctions, have been proposed and analyzed in the economics literature. We compare the usefulness of different mechanisms for on-line auctions, focusing on the cognitive costs placed on users (e.g. the cost of determining the value of a good), the possibilities for agent mediation, and the trust properties of the auction. Different auction formats prove to be attractive for agent mediated on-line auctions than for traditional off-line auctions. For example, second price sealed bid auctions are attractive in traditional auctions because they avoid the communication cost of multiple bids in first price ascending auctions, and the âgamingâ required to estimate the second highest bid in first price sealed bid auctions. However, when bidding agents are cheap, communication costs cease to be important, and a progressive auction mechanism is preferred over a closed bid auction mechanism, since users with semi-autonomous agents can avoid the cognitive cost of placing an accurate value on a good. As another example, when an on-line auction is being conducted by an untrusted auctioneer (e.g. the auctioneer is selling its own items), rational participants will build bidding agents that transform second price auctions into first price auctions.Engineering and Applied Science
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