Abstract
We attend to the classic setting where an observer needs to inform a tracker about an arbitrary time varying function f: ℕ0 →ℤ. This is an optimization problem, where both wrong values at the tracker and sending updates entail a certain cost. We consider an online variant of this problem, i.e., at time t, the observer only knows f(t′) for all t′ ≤ t. In this paper, we generalize existing cost models (with an emphasis on concave and convex penalties) and present two online algorithms. Our analysis shows that these algorithms perform well in a large class of models, and are even optimal in some settings.
Supported by MNiSW grants number N N206 2573 35 and N N206 1723 33.
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Bienkowski, M., Schmid, S. (2010). Online Function Tracking with Generalized Penalties. In: Kaplan, H. (eds) Algorithm Theory - SWAT 2010. SWAT 2010. Lecture Notes in Computer Science, vol 6139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13731-0_34
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DOI: https://doi.org/10.1007/978-3-642-13731-0_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13730-3
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