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