Adaptive online time allocation to search algorithms

Matteo Gagliolo, Viktor Zhumatiy, Jürgen Schmidhuber

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

Given is a search problem or a sequence of search problems, as well as a set of potentially useful search algorithms. We propose a general framework for online allocation of computation time to search algorithms based on experience with their performance so far. In an example instantiation, we use simple linear extrapolation of performance for allocating time to various simultaneously running genetic algorithms characterized by different parameter values. Despite the large number of searchers tested in parallel, on various tasks this rather general approach compares favorably to a more specialized state-of-the-art heuristic; in one case it is nearly two orders of magnitude faster. © Springer-Verlag Berlin Heidelberg 2004.
Original languageEnglish (US)
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
PublisherSpringer Verlag
Pages134-143
Number of pages10
DOIs
StatePublished - Jan 1 2004
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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