An investigation of exploitation versus exploration in GBEA optimization of PORS 15 and 16 Problems

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It was hypothesized that the variations in time to solution are driven by the competing mechanisms of exploration and exploitation.This thesis explores this hypothesis by examining two contrasting problems that embody the hypothesized tradeoff between exploration and exploitation. Plus one recall store (PORS) is an optimization problem based on the idea of a simple calculator with four buttons: plus, one, store, and recall. Integer addition and store are classified as operations, and one and memory recall are classified as terminals. The goal is to arrange a fixed number of keystrokes in a way that maximizes the numerical result. PORS 15 ... continued below

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Koch, Kaelynn May 8, 2012.

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This thesis or dissertation is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 40 times . More information about this document can be viewed below.

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  • Ames Laboratory
    Publisher Info: Ames Laboratory (AMES), Ames, IA (United States)
    Place of Publication: Ames, Iowa

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It was hypothesized that the variations in time to solution are driven by the competing mechanisms of exploration and exploitation.This thesis explores this hypothesis by examining two contrasting problems that embody the hypothesized tradeoff between exploration and exploitation. Plus one recall store (PORS) is an optimization problem based on the idea of a simple calculator with four buttons: plus, one, store, and recall. Integer addition and store are classified as operations, and one and memory recall are classified as terminals. The goal is to arrange a fixed number of keystrokes in a way that maximizes the numerical result. PORS 15 (15 keystrokes) represents the subset of difficult PORS problems and PORS 16 (16 keystrokes) represents the subset of PORS problems that are easiest to optimize. The goal of this work is to examine the tradeoff between exploitation and exploration in graph based evolutionary algorithm (GBEA) optimization. To do this, computational experiments are used to examine how solutions evolve in PORS 15 and 16 problems when solved using GBEAs. The experiment is comprised of three components; the graphs and the population, the evolutionary algorithm rule set, and the example problems. The complete, hypercube, and cycle graphs were used for this experiment. A fixed population size was used.

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  • Report No.: IS-T 3056
  • Grant Number: DE-AC02-07CH11358
  • DOI: 10.2172/1048523 | External Link
  • Office of Scientific & Technical Information Report Number: 1048523
  • Archival Resource Key: ark:/67531/metadc839911

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Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • May 8, 2012

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  • May 19, 2016, 9:45 a.m.

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  • Aug. 3, 2016, 4:03 p.m.

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Koch, Kaelynn. An investigation of exploitation versus exploration in GBEA optimization of PORS 15 and 16 Problems, thesis or dissertation, May 8, 2012; Ames, Iowa. (digital.library.unt.edu/ark:/67531/metadc839911/: accessed January 16, 2019), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.