Tight Bounds for Blind Search on the Integers

Authors Martin Dietzfelbinger, Jonathan E. Rowe, Ingo Wegener, Philipp Woelfel



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Martin Dietzfelbinger
Jonathan E. Rowe
Ingo Wegener
Philipp Woelfel

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Martin Dietzfelbinger, Jonathan E. Rowe, Ingo Wegener, and Philipp Woelfel. Tight Bounds for Blind Search on the Integers. In 25th International Symposium on Theoretical Aspects of Computer Science. Leibniz International Proceedings in Informatics (LIPIcs), Volume 1, pp. 241-252, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008) https://doi.org/10.4230/LIPIcs.STACS.2008.1348

Abstract

We analyze a simple random process in which a token is moved in the
   interval $A={0,dots,n$: Fix a probability distribution $mu$
   over ${1,dots,n$.  Initially, the token is placed in a random
   position in $A$.  In round $t$, a random value $d$ is chosen
   according to $mu$.  If the token is in position $ageq d$, then it
   is moved to position $a-d$.  Otherwise it stays put.  Let $T$ be
   the number of rounds until the token reaches position 0.  We show
   tight bounds for the expectation of $T$ for the optimal
   distribution $mu$.  More precisely, we show that
   $min_mu{E_mu(T)=Thetaleft((log n)^2
ight)$.  For the
   proof, a novel potential function argument is introduced.  The
   research is motivated by the problem of approximating the minimum
   of a continuous function over $[0,1]$ with a ``blind'' optimization
   strategy.

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