Job-Level Alpha-Beta Search

An approach called generic job-level (JL) search was proposed to solve computer game applications by dispatching jobs to remote workers for parallel processing. This paper applies JL search to alpha-beta search, and proposes a JL alpha-beta search (JL-ABS) algorithm based on a best-first search vers...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on computational intelligence and AI in games. 2015-03, Vol.7 (1), p.28-38
Main Authors: Chen, Jr-Chang, Wu, I-Chen, Tseng, Wen-Jie, Lin, Bo-Han, Chang, Chia-Hui
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Alpha-beta search
chinese chess
Complexity theory
Computer science
Computers
Educational institutions
game tree search
Games
job-level computing
opening book
Parallel processing
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An approach called generic job-level (JL) search was proposed to solve computer game applications by dispatching jobs to remote workers for parallel processing. This paper applies JL search to alpha-beta search, and proposes a JL alpha-beta search (JL-ABS) algorithm based on a best-first search version of MTD(f). The JL-ABS algorithm is demonstrated by using it in an opening book analysis for Chinese chess. The experimental results demonstrated that JL-ABS reached a speed-up of 10.69 when using 16 workers in the JL system.
ISSN:1943-068X
1943-0698
DOI:10.1109/TCIAIG.2014.2316314