Open-Ended Behavioral Complexity for Evolved Virtual Creatures

被引:0
|
作者
Lessin, Dan [1 ]
Fussell, Don [1 ]
Miikkulainen, Risto [1 ]
机构
[1] Univ Texas Austin, Dept Comp Sci, Austin, TX 78712 USA
来源
GECCO'13: PROCEEDINGS OF THE 2013 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE | 2013年
关键词
evolved virtual creatures; artificial life; physics-based character animation; task decomposition; content creation; SYSTEM;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the 19 years since Karl Sims' landmark publication on evolving virtual creatures [22], much of the future work he proposed has been implemented, having a significant impact on multiple fields including graphics, evolutionary computation, and artificial life. There has, however been one notable exception to this progress. Despite the potential benefits, there has been no clear increase in the behavioral complexity of evolved virtual creatures (EVCs) beyond the light following demonstrated in Sims' original work. This paper presents an open-ended method to move beyond this limit, making use of high-level human input in the form of a syllabus of intermediate learning tasks-along with mechanisms for preservation, reuse, and combination of previously learned tasks. This method (named ESP for its three components: encapsulation, syllabus, and pandemonium) is employed to evolve a virtual creature with behavioral complexity that clearly exceeds previously achieved levels. ESP thus demonstrates that EVCs may indeed have the potential to one day rival the behavioral complexity- and therefore the entertainment value-of their non-virtual counterparts.
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页码:335 / 342
页数:8
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