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Author Prakash, Edmond C. ♦ Loh, Peter K. K.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Performance simulation ♦ Moving target search ♦ Game ai ♦ Fuzzy ♦ Abstraction
Abstract In a computer game, equipping a bot with a suitable algorithm to locate a human player is difficult. Besides the unpredictable moves made by the player, an unexplored map region poses additional constraints such as new obstacles and pathways that the bot needs to discover quickly. The design criteria of such moving target search (MTS) algorithms would typically need to consider computation efficiency and storage requirements. That is, the bot must appear to be “smart” and “quick” in order to enhance the playability and challenge posed by the game. These criteria, however, pose conflicting requirements. In this article, we study and evaluate the performance and behavior of two novel MTS algorithms, Fuzzy MTS and Abstraction MTS, against existing MTS algorithms in randomly generated mazes of increasing size. Simulations reveal that Fuzzy MTS and Abstraction MTS exhibit competitive performance even with large problem spaces.
Description Affiliation: Manchester Metropolitan University, Manchester, UK (Prakash, Edmond C.) || Nanyang Technological University, Singapore (Loh, Peter K. K.)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-03-01
Publisher Place New York
Journal Computers in Entertainment (CIE) (CIE)
Volume Number 7
Issue Number 2
Page Count 16
Starting Page 1
Ending Page 16


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Source: ACM Digital Library