DocumentCode :
1822462
Title :
Intelligent self-learning characters for computer games
Author :
Tang, Wen ; Wan, Tao Ruan
Author_Institution :
Sch. of Comput. & Math., Univ. of Teeside, Middlesborough, UK
fYear :
2002
fDate :
2002
Firstpage :
51
Lastpage :
58
Abstract :
In this paper, a novel AI-based animation approach is presented to simulate intelligent self-learning characters for computer games or other interactive virtual reality applications. The complex learning behaviours of the virtual characters are modelled as an evolutionary process so that adaptive AI algorithms such as genetic algorithms have been used to simulate the learning process. The simulation method enables the characters in a computer game environment to have abilities to learn for specific assigned tasks. Its skill for completing the tasks can be developed and evolved through its experiences of performing the tasks. The paper also describes techniques for performance evaluation and optimisation for virtual characters to perform jumping tasks.
Keywords :
artificial intelligence; computer animation; computer games; genetic algorithms; unsupervised learning; virtual reality; AI-based animation; computer games; genetic algorithms; intelligent self-learning characters; interactive virtual reality applications; jumping tasks; learning; performance evaluation; virtual characters; Animation; Application software; Artificial intelligence; Computational modeling; Computer simulation; Games; Genetic algorithms; Humans; Learning; Muscles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Eurographics UK Conference, 2002. Proceedings. The 20th
Print_ISBN :
0-7695-1518-5
Type :
conf
DOI :
10.1109/EGUK.2002.1011272
Filename :
1011272
Link To Document :
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