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Logical Prior Probability

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Artificial General Intelligence (AGI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7716))

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Abstract

A Bayesian prior over first-order theories is defined. It is shown that the prior can be approximated, and the relationship to previously studied priors is examined.

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References

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Author information

Authors and Affiliations

  1. Institute for Creative Technologies, 12015 Waterfront Drive, Playa Vista, CA, 90094, USA

    Abram Demski

Authors
  1. Abram Demski
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Editor information

Editors and Affiliations

  1. Humboldt Universität Berlin, Raumerstr. 11, 10437, Berlin, Germany

    Joscha Bach

  2. Aidyia Ltd., Unit 612, 6/F, Lu Plaza, 2 Wing Yip Street, Kwun Tong, Hong Kong

    Ben Goertzel

  3. Adams State University, Suite 3060, 81101, Alamosa, CO, USA

    Matthew Iklé

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© 2012 Springer-Verlag Berlin Heidelberg

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Demski, A. (2012). Logical Prior Probability. In: Bach, J., Goertzel, B., Iklé, M. (eds) Artificial General Intelligence. AGI 2012. Lecture Notes in Computer Science(), vol 7716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35506-6_6

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  • DOI: https://doi.org/10.1007/978-3-642-35506-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35505-9

  • Online ISBN: 978-3-642-35506-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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