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Journal of Computer and System Sciences
Article
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Journal of Computer and System Sciences
Article . 1997
License: Elsevier Non-Commercial
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Journal of Computer and System Sciences
Article . 1997 . Peer-reviewed
License: Elsevier Non-Commercial
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zbMATH Open
Article . 1997
Data sources: zbMATH Open
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Article . 1997
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The Discovery of Algorithmic Probability

The discovery of algorithmic probability
Authors: Ray J. Solomonoff;

The Discovery of Algorithmic Probability

Abstract

This paper will describe a voyage of discovery — the discovery of Algorithmic Probability. But before I describe that voyage —a few words about motivation. Motivation in science is roughly of two kinds: In one, the motivation is discovery itself — the joy of “going where no one has gone before” — the excitement of creating new universes and exploring them. Another kind of motivation is the achievement of a previously defined larger goal, and there may be many subsidiary discoveries on the path to this goal. In my own case both kinds of motivation were very strong. I first experienced the pure joy of mathematical discovery when I was very young — learning algebra. I didn’t really see why one of the axioms was “obvious”, so I tried reversing it and exploring the resultant system. For a few hours I was in this wonderful never-never land that I myself had created! The joy of exploring it only lasted until it became clear that my new axiom wouldn’t work, but the motivation of the joy of discovery continued for the rest of my life. The motivation for the discovery of Algorithmic Probability was somewhat different. It was the result of “goal motivated discovery” — like the discovery of the double helix in biology, but with fewer people involved and relatively little political skullduggery. The goal I set grew out of my early interest in science and mathematics. I found that while the discoveries of the past were interesting to me, I was

Keywords

Computational Theory and Mathematics, Computer Networks and Communications, Analysis of algorithms and problem complexity, Applied Mathematics, Theoretical Computer Science

  • BIP!
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    The total number of citations received by all articles of the researcher of interest.
    69
    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
69
Top 10%
Top 10%
Average
hybrid