Date of Award:
5-2013
Document Type:
Thesis
Degree Name:
Master of Computer Science (MCS)
Department:
Computer Science
Committee Chair(s)
Daniel Bryce
Committee
Daniel Bryce
Committee
Dan Watson
Committee
Scott Cannon
Abstract
Search is an important aspect of Artificial Intelligence. Efficiently searching for solutions to large problems is important. One way to scale search large in problems quickly is to divide the work between multiple processors. There are many ways to divide this work using abstractions. This thesis examines the previous way this has been done in the past and introduces other ways to more efficiently divide the work and search in parallel.
Checksum
8ee015990d94c316272e441e045c44da
Recommended Citation
Redd, Justin R., "The Effects of Abstraction on Best NBlock First Search" (2013). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 1476.
https://digitalcommons.usu.edu/etd/1476
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