On the Computational Measurement of Intelligence Factors

作者: José Hernández-Orallo

DOI:

关键词: Scale (ratio)Theoretical computer scienceComputer science

摘要: In this paper we develop a computational framework for the measurement of different factors or abilities which are usually found in intelligent behaviours. For this, first scale measuring complexity an instance problem, depending on descriptional (Levin LT variant) ‘explanation’ answer to problem. We centre establishment either deductive and inductive abilities, show that their evaluation settings special cases general framework. Some classical dependencies between them shown way separate these is developed. Finally, some variants previous other possible ones be taken into account investigated. end, application measurements AI progress discussed.

参考文章(18)
Jose Hernandez-Orallo, Computational measures of information gain and reinforcement in inference processes Ai Communications. ,vol. 13, pp. 49- 50 ,(2000)
Geoff Sutcliffe, Christian Suttner, The TPTP Problem Library Journal of Automated Reasoning. ,vol. 21, pp. 177- 203 ,(1998) , 10.1023/A:1005806324129
E Mark Gold, Language identification in the limit Information & Computation. ,vol. 10, pp. 447- 474 ,(1967) , 10.1016/S0019-9958(67)91165-5
Gregory J. Chaitin, Gödel's theorem and information International Journal of Theoretical Physics. ,vol. 21, pp. 941- 954 ,(1982) , 10.1007/BF02084159
A. N. Kolmogorov, Three approaches to the quantitative definition of information International Journal of Computer Mathematics. ,vol. 2, pp. 157- 168 ,(1968) , 10.1080/00207166808803030
Gilbert H. Harman, The Inference to the Best Explanation The Philosophical Review. ,vol. 74, pp. 88- ,(1965) , 10.2307/2183532
R. Solomonoff, Two Kinds of Probabilistic Induction The Computer Journal. ,vol. 42, pp. 256- 259 ,(1999) , 10.1093/COMJNL/42.4.256
R. Solomonoff, Complexity-based induction systems: Comparisons and convergence theorems IEEE Transactions on Information Theory. ,vol. 24, pp. 422- 432 ,(1978) , 10.1109/TIT.1978.1055913