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)


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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