The Application Of Algorithmic Probability to Problems in Artificial Intelligence (1986)
| Venue: | in Uncertainty in Artificial Intelligence, Kanal, L.N. and Lemmer, J.F. (Eds), Elsevier Science Publishers B.V |
| Citations: | 24 - 4 self |
BibTeX
@INPROCEEDINGS{Solomonoff86theapplication,
author = {Ray Solomonoff},
title = {The Application Of Algorithmic Probability to Problems in Artificial Intelligence},
booktitle = {in Uncertainty in Artificial Intelligence, Kanal, L.N. and Lemmer, J.F. (Eds), Elsevier Science Publishers B.V},
year = {1986},
pages = {473--491},
publisher = {Elsevier Science Publishers}
}
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Abstract
INTRODUCTION We will cover two topics First, Algorithmic Probability --- the motivation for defining it, how it overcomes di#culties in other formulations of probability, some of its characteristic properties and successful applications. Second, we will apply it to problems in A.I. --- where it promises to give near optimum search procedures for two very broad classes of problems. A strong motivation for revising classical concepts of probability has come from the analysis of human problem solving. When working on a di#cult problem, a person is in a maze in which he must make choices of possible courses of action. If the problem is a familiar one, the choices will all be easy. If it is not familiar, there can be much uncertainty in each choice, but choices must somehow be made. One basis for choice might be the probability of each choice leading to a quick solution --- this probability being based on experience in this problem and in problems like it. A good reason for using proba
