Beyond the turing test: Performance metrics for evaluating a computer simulation of the human mind

被引:2
作者
Alvarado, N [1 ]
Adams, SS [1 ]
Burbeck, S [1 ]
Latta, C [1 ]
机构
[1] IBM Corp, Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA
来源
2ND INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING, PROCEEDINGS | 2002年
关键词
D O I
10.1109/DEVLRN.2002.1011826
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Performance metrics for machine intelligence (e.g., the Turing test) have traditionally consisted of pass/fail tests. Because the tests devised by psychologists have been aimed at revealing unobservable processes of human cognition, they are similarly capable of revealing how a computer accomplishes a task, not simply its success or failure. Here we adapt a set of tests of abilities previously measure in humans to be used as a benchmark for simulation of human cognition. Our premise is that if a machine cannot pass these tests, it is unlikely to be able to engage in the more complex cognition routinely exhibited by animals and humans. If it cannot pass these tests, it will lack fundamental capabilities underlying such performance.
引用
收藏
页码:147 / 152
页数:6
相关论文
共 13 条
[1]  
[Anonymous], LEARNING PRINCIPLES
[2]  
BERSCHEID E, 1989, REV PERSONALITY SOCI, V10, P63
[3]  
Bower G.H., 1981, Theories of learning
[4]  
BREAZEAL C, 2001, IN PRESS DESIGNING S
[5]  
Carver C. S., 1981, Attention and self-regulation: A control-theory approach to human behavior
[6]  
Fiske ST., 1991, SOC COGNITION
[7]  
Langer J., 2001, LANGUAGE ACQUISITION
[8]  
Loebner H., LOEBNER PRIZE
[9]  
SEARLE JR, 1980, BEHAV BRAIN SCI, V3, P417, DOI 10.1017/S0140525X00006038
[10]  
Smith L. B., 2001, LANGUAGE ACQUISITION