On the Complexity of Causal Models

作者: B. R. Gaines

DOI: 10.1109/TSMC.1976.5408397

关键词:

摘要: It is argued that a principle of casuality fundamental to human thinking, and it has been observed experimentally this assumption leads complex hypothesis formation by subjects attempting solve comparatively simple problems involving acausal randomly generated events. This correspondence provides an automatatheoretic explanation phenomenon analyzing the performance optimal modeler observing behavior system forming minimal-state model it.

参考文章(11)
Albert Michotte, The perception of causality ,(1963)
Gregory J. Chaitin, On the Length of Programs for Computing Finite Binary Sequences Journal of the ACM. ,vol. 13, pp. 547- 569 ,(1966) , 10.1145/321356.321363
J.H. Andreae, P.M. Cashin, A learning machine with monologue International Journal of Human-computer Studies \/ International Journal of Man-machine Studies. ,vol. 1, pp. 1- 20 ,(1969) , 10.1016/S0020-7373(69)80008-8
A. Kolmogorov, Logical basis for information theory and probability theory IEEE Transactions on Information Theory. ,vol. 14, pp. 662- 664 ,(1968) , 10.1109/TIT.1968.1054210
David G. Willis, Computational Complexity and Probability Constructions Journal of the ACM. ,vol. 17, pp. 241- 259 ,(1970) , 10.1145/321574.321578
Per Martin-Löf, The definition of random sequences Information & Computation. ,vol. 9, pp. 602- 619 ,(1966) , 10.1016/S0019-9958(66)80018-9
B.R. Gaines, Memory minimisation in control with stochastic automata Electronics Letters. ,vol. 7, pp. 710- 711 ,(1971) , 10.1049/EL:19710487
J. M. Jauch, Determinism in Classical and Quantal Physics Dialectica. ,vol. 27, pp. 13- 26 ,(1973) , 10.1111/J.1746-8361.1973.TB00610.X