Title :
Job-Level Alpha-Beta Search
Author :
Jr-Chang Chen ; I-Chen Wu ; Wen-Jie Tseng ; Bo-Han Lin ; Chia-Hui Chang
Author_Institution :
Dept. of Appl. Math., Chung Yuan Christian Univ., Chungli, Taiwan
Abstract :
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.
Keywords :
computer games; search problems; Chinese chess; JL-ABS algorithm; best-first search version; computer game application; job-level alpha-beta search; Algorithm design and analysis; Complexity theory; Computer science; Computers; Educational institutions; Games; Parallel processing; Alpha-beta search; chinese chess; game tree search; job-level computing; opening book;
Journal_Title :
Computational Intelligence and AI in Games, IEEE Transactions on
DOI :
10.1109/TCIAIG.2014.2316314
