24,157 research outputs found
Copyright, Culture, and Community in Virtual Worlds
Communities that interact on-line through computer games and other virtual worlds are mediated by the audiovisual content of the game interface. Much of this content is subject to copyright law, which confers on the copyright owner the legal right to prevent certain unauthorized uses of the content. Such exclusive rights impose a limiting factor on the development of communities that are situated around the interface content, because the rights, privileges, and\ud
exceptions associated with copyright generally tend to disregard the cultural significance of copyrighted content. This limiting effect of copyright is well illustrated by examination of the copied content appropriated by virtual diaspora communities from the game Uru: Ages of Myst. Reconsideration of current copyright law would be required in order to accommodate the cohesion of on-line\ud
communities and related cultural uses of copyrighted content
Strongly Polynomial Primal-Dual Algorithms for Concave Cost Combinatorial Optimization Problems
We introduce an algorithm design technique for a class of combinatorial
optimization problems with concave costs. This technique yields a strongly
polynomial primal-dual algorithm for a concave cost problem whenever such an
algorithm exists for the fixed-charge counterpart of the problem. For many
practical concave cost problems, the fixed-charge counterpart is a well-studied
combinatorial optimization problem. Our technique preserves constant factor
approximation ratios, as well as ratios that depend only on certain problem
parameters, and exact algorithms yield exact algorithms.
Using our technique, we obtain a new 1.61-approximation algorithm for the
concave cost facility location problem. For inventory problems, we obtain a new
exact algorithm for the economic lot-sizing problem with general concave
ordering costs, and a 4-approximation algorithm for the joint replenishment
problem with general concave individual ordering costs
Separable Concave Optimization Approximately Equals Piecewise-Linear Optimization
We study the problem of minimizing a nonnegative separable concave function
over a compact feasible set. We approximate this problem to within a factor of
1+epsilon by a piecewise-linear minimization problem over the same feasible
set. Our main result is that when the feasible set is a polyhedron, the number
of resulting pieces is polynomial in the input size of the polyhedron and
linear in 1/epsilon. For many practical concave cost problems, the resulting
piecewise-linear cost problem can be formulated as a well-studied discrete
optimization problem. As a result, a variety of polynomial-time exact
algorithms, approximation algorithms, and polynomial-time heuristics for
discrete optimization problems immediately yield fully polynomial-time
approximation schemes, approximation algorithms, and polynomial-time heuristics
for the corresponding concave cost problems.
We illustrate our approach on two problems. For the concave cost
multicommodity flow problem, we devise a new heuristic and study its
performance using computational experiments. We are able to approximately solve
significantly larger test instances than previously possible, and obtain
solutions on average within 4.27% of optimality. For the concave cost facility
location problem, we obtain a new 1.4991+epsilon approximation algorithm.Comment: Full pape
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