209 research outputs found
Defending Elections Against Malicious Spread of Misinformation
The integrity of democratic elections depends on voters' access to accurate
information. However, modern media environments, which are dominated by social
media, provide malicious actors with unprecedented ability to manipulate
elections via misinformation, such as fake news. We study a zero-sum game
between an attacker, who attempts to subvert an election by propagating a fake
new story or other misinformation over a set of advertising channels, and a
defender who attempts to limit the attacker's impact. Computing an equilibrium
in this game is challenging as even the pure strategy sets of players are
exponential. Nevertheless, we give provable polynomial-time approximation
algorithms for computing the defender's minimax optimal strategy across a range
of settings, encompassing different population structures as well as models of
the information available to each player. Experimental results confirm that our
algorithms provide near-optimal defender strategies and showcase variations in
the difficulty of defending elections depending on the resources and knowledge
available to the defender.Comment: Full version of paper accepted to AAAI 201
Network Dimensioning with Maximum Revenue Efficiency for the Fairness Index, Journal of Telecommunications and Information Technology, 2016, nr 4
Network dimensioning is a specific kind of the resource allocation problem. One of the tasks in the network optimization is to maximize the total flow on given pairs of nodes (so-called demands or paths between source and target). The task can be more complicated when different revenue/profit gained from each unit of traffic stream allocated on each demand is taken into account. When the total revenue is maximized the problem of starvation of less attractive paths can appear. Therefore, it is important to include some fairness criteria to preserve connections between all the demands on a given degree of quality, also for the least attractive paths. In this paper, a new bicriteria ratio optimization method which takes into account both, the revenue and the fairness is proposed. Mathematical model is built in a form of linear programming. The solutions are analyzed with some statistical measures to evaluate their quality, with respect to fairness and efficiency. In particular, the Gini’s coefficient is used for this purpose
Handling Scheduling Problems with Controllable Parameters by Methods of Submodular Optimization
In this paper, we demonstrate how scheduling problems with controllable processing times can be reformulated as maximization linear programming problems over a submodular polyhedron intersected with a box. We explain a decomposition algorithm for solving the latter problem and discuss its implications for the relevant problems of preemptive scheduling on a single machine and parallel machines
A REVIEW OF APPLICATIONS OF MULTIPLE - CRITERIA DECISION-MAKING TECHNIQUES TO FISHERIES
Management of public resources, such as fisheries, is a complex task. Society, in general, has a number of goals that it hopes to achieve from the use of public resources. These include conservation, economic, and social objectives. However, these objectives often conflict, due to the varying opinions of the many stakeholders. It would appear that the techniques available in the field of multiple-criteria decision-making (MCDM) are well suited to the analysis and determination of fisheries management regimes. However, to date, relatively few publications exist using such MCDM methods compared to other applicational fields, such as forestry, agriculture, and finance. This paper reviews MCDM applied to fishery management by providing an overview of the research published to date. Conclusions are drawn regarding the success and applicability of these techniques to analyzing fisheries management problems.Resource /Energy Economics and Policy,
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